Book Chapters

  • 古月 敬之, "第21章 21.1 自己組織化機能局在型ニューラルネットワーク", 電気学会編,「進化技術ハンドブック 第II卷応用編:情報・通信システム」,pp.396-401,東京,近代科学社,11,2011.
  • 古月 敬之, "第21章 21.4 非線形多項式モデルの同定", 電気学会編,「進化技術ハンドブック 第II卷応用編:情報・通信システム」,pp.414-419,東京,近代科学社,11,2011.
  • B. Chen and J.Hu, "Protein Structure Prediction Based on HP Model Using an Improved Hybrid EDA", in book entitled Exploitation of Linkage Learning in Evolutionary Algorithms - ALO3,  Y.P. Chen, Eds, pp.193-214, Springer-Verlag, Berlin, GERMANY, 2010.
  • 古月 敬之, "第二章 線形特性を有するニューラルネットワーク", 渡辺桂吾編著, 「ニューラルネットワーク計算知能」, pp.27-49, 森北出版株式会社, 東京, 2006
  • J.Hu and K.Hirasawa, "A Method for Applying Neural Networks to Control of Nonlinear Systems", in book entitled Neural Information Processing: Research and Development, J.C.Rajapakse and L.Wang, Eds, pp.351-369, Springer, Berlin, GERMANY, 2004.
  • K.Kumamaru, J.Hu, K.Inoue and T.Soderstrom, " Statistical Methods for Robust Change Detection in Dynamical Systems with Model Uncertainty ", in book entitled Statistical Methods in Control and Signal Processing, T. Katayama and S. Sugimoto, Eds., pp.453-479, Mercel Dekker Inc., New York, USA, 1997.

2023 Journal Papers

  • B. Zhou, B. Chen and J. Hu, "Authors' reply to the comments by Kamata et al (Letter)", IEICE Trans. on Fundamentals of Electronics, communications and Computer Sciences, Vol.E106-A, No.11, pp.1-4, Nov., 2023 doi
  • D. Li and J. Hu, "Understanding Pedestrian Trajectory Prediction from the Planning Perspective", IEEJ Trans. on Electrical and Electronic Engineering, Vol.18, No.10, October, 2023. doi
  • X. Fu, H. Deng and J. Hu, "Automatic Label Calibration for Singing Annotation Using Fully Convolution Neural Network", IEEJ Trans. on Electrical and Electronic Engineering, Vol.18, No.6, pp.945-952, June, 2023. doi

2023 Proceeding Papers

2022 Journal Papers

  • H. Zhu and J. Hu, "An Improved Hybrid Model for Nonlinear Regression with Missing Values Using Deep Quasi-Linear Kernel", IEEJ Trans. on Electrical and Electronic Engineering, Vol.17, No.10, pp.1460-1468, October, 2022. doi
  • J. Wu and J. Hu, "Redefining Prior Feature Space via Finetuning a Triplet Network for Few-Shot Learning", IET Computer Vision, Vol.16, No.6, pp.514-524, September, 2022. doi
  • X. Fu, H. Deng, X. Yuan and J. Hu, "Generating High Coherence Monophonic Music Using Monte-Carlo Tree Search", IEEE Trans. on Multimedia, 2022. doi
  • H. Deng, X. Yuan, Y. Tian and J. Hu, "Neural-Augmented Two-Stage Monte Carlo Tree Search with Over-Sampling for Protein Folding in HP Model", IEEJ Trans. on Electrical and Electronic Engineering, Vol.17, No.5, pp.685-694, May, 2022. doi
  • H. Deng, Y. Tian, J. Luo and J. Hu, "Relation-Level User Behavior Modeling for Click-Through Rate Prediction", IEEJ Trans. on Electrical and Electronic Engineering, Vol.17, No.3, pp.398-406, March, 2022. doi
  • Y. Ren, H. Jiang, H. Zhu, Y. Tian and J. Hu, "A Semi-Supervised Classification Method of Parasites Using Contrastive Learning", IEEJ Trans. on Electrical and Electronic Engineering, Vol.17, No.3, pp.445-453, March, 2022. doi
  • X. Yuan, H. Deng and J. Hu, "Constructing a PPI Network Based on Deep Transfer Learning for ProteinComplex Detection", IEEJ Trans. on Electrical and Electronic Engineering, Vol.17, No.3, pp.436-444, March, 2022. doi
  • J. Wu and J. Hu, "Improved Prior Selection Using Semantics in Maximum A Posteriori for Few-Shot Learning", Knowledge-Based Systems, 237(2022) 107688, pp.1-11, February, 2022. doi

2022 Proceeding Papers

  • X. Fu, X. Yuan and J. Hu, "HSD: A hierarchical singing annotation dataset", in Proc. of 2022 IEEE International Symposium on Multimedia (ISM 2022), Dec., 2022, pp.245-246. doi
  • J. Wu and J. Hu, "Learning a Latent Space with Triplet Network for Few-Shot Image Classification", in Proc. of Inter. Conference on Pattern Recognition (ICPR 2022) Montreal), August, 2022, pp.5038-5044. doi
  • H. Deng and J. Hu, "Improving Sequential Recommendation via Subsequence Extraction", in Proc. of 2021 IEEE International Joint Conference on Neural Networks (IJCNN 2022), July, 2022, pp.1-7. doi

2021 Journal Papers

  • H. Zhu, Y. Ren, Y. Tian and J. Hu, "A Winner-Take-All Autoencoder Based Piecewise Linear Model for Nonlinear Regression with Missing Data", IEEJ Trans. on Electrical and Electronic Engineering, Vol.16, No.12, pp.1618-1627, Dec, 2021. doi
  • J. Luo, R. Rui, J. Hu and D.E. Baz, "Combating the Infodemic: A Chinese Infodemic Dataset for Misinformation Identification", Healthcare 2021, 9(9) 1090. pp.1-13, September, 2021. doi
  • J. Wu, N. Dong, F. Liu, S. Yang and J. Hu, "Feature Hallucination via Maximum A Posteriori for Few-Shot Learning", Knowledge-Based Systems, 225(2021) 107129. pp.1-10, August, 2021. doi
  • X. Yuan, E. Pang, K. Lin and J. Hu, "Deep Protein Subcellular Localization Predictor Enhanced with Transfer Learning of GO Annotation", IEEJ Trans. on Electrical and Electronic Engineering, Vol.16, No.4, April, 2021. doi
  • Y. Ren, H. Zhu, Y. Tian and J. Hu, "A Laplacian SVM Based Semi-Supervised Classification Using Multi-Local Linear Model", IEEJ Trans. on Electrical and Electronic Engineering, Vol.16, No.3, pp.455-463, March, 2021. doi

2021 Proceeding Papers

  • X. Yuan, H. Deng and J. Hu, "Deep Transfer Learning Based PPI Prediction for Protein Complex Detection", in Proc. of 2021 IEEE International Conference on System, Man, and Cybernetics (SMC 2021) (Virtual), Oct., 2021, pp.321-326. doi
  • H. Zhu, Y. Ren and J. Hu, "Establishing a Hybrid Piecewise Linear Model for Air Quality Prediction Based Missingness Challenges", in Proc. of 2021 IEEE International Conference on System, Man, and Cybernetics (SMC 2021) (Virtual), Oct., 2021, pp.1705-1710. doi
  • Y. Ren, H. Deng, H. Jiang and J. Hu, "A Semi-Supervised Classification Method of Apicomplexan Parasites and Host Cell Using Contrastive Learning Strategy", in Proc. of 2021 IEEE International Conference on System, Man, and Cybernetics (SMC 2021) (Virtual), Oct., 2021, pp.2973-2978. doi
  • R. Su, W. Huang, H. Ma, X. Song and J. Hu, "SGE Net: Video Object Detection with Squeezed GRU and Information Entropy Map", in Proc. of 2021 IEEE International Conference on Image Processing (ICIP 2021) (Anchorage), Sept., 2021. doi
  • H. Deng, J. Luo and J. Hu, "Attention Relation Network for Object Based Video Games", in Proc. of 2021 IEEE International Joint Conference on Neural Networks (IJCNN 2021), July, 2021. doi

2020 Journal Papers

  • H. Zhu, Y. Tian, Y. Ren and J. Hu, "A Hybrid Model for Nonlinear Regression with Missing Data Using Quasi-Linear Kernel", IEEJ Trans. on Electrical and Electronic Engineering, Vol.15, No.12, pp.1791-1800, Dec, 2020. doi
  • J. Luo, R. Xue and J. Hu, "COVID-19 infodemic on Chinese social media: A 4P framework, selective review and research directions", Measurement and Control, Vol.53, No.9-10, pp.2070-2079, Nov, 2020. doi
  • X. Yuan, E. Pang, K. Lin and J. Hu, "Hierarchical Multi-label Classification for Gene Ontology Annotation using Multi-head and Multi-end Deep CNN Model", IEEJ Trans. on Electrical and Electronic Engineering, Vol.15, No.7, pp.1057-1064, July, 2020. doi
  • Y. Ren, W.Li and J. Hu, "A Semi-Supervised Classifier Based on Piecewise Linear Regression Model Using Gated Linear Network", IEEJ Trans. on Electrical and Electronic Engineering, Vol.15, No.7, pp.1048-1056, July, 2020. doi
  • J. Luo, D.E. Baz, R. Xue and J. Hu, "Solving the dynamic energy aware job shop scheduling problem with the heterogeneous parallel genetic algorithm", Future Generation Computer Systems, Vol.108, pp.119-134, July, 2020. doi
  • W. Zou, S. Zou, D. He, J. Hu and Y. Yu, "SpeckleNoise Reduction of Holograms Based on Spectral ConvolutionalNeural Network (in Chinese)", Acta Optica Sinica (光学学报), Vol.40, No.5, pp.1-8, March, 2020. doi
  • P. Liang, W. Li and J. Hu, "Fast SVM Training using Data Reconstruction for Classification of Very Large Datasets", IEEJ Trans. on Electrical and Electronic Engineering, Vol.15, No.3, pp.372-381, March, 2020. doi

2020 Proceeding Papers

  • C. Tang, Y. Kuang, J. Lv and J. Hu, "SAN: Sampling Adversarial Networks for Zero-Shot Learning", in Proc. of International Conference on Neural Information Processing (ICONIP 2020), Nov., 2020, pp626-638. doi
  • Y. Yi, H. Deng and J. Hu, "Improving Image Captioning Evaluation by Considering Inter References Variance", in Proc. of the 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020) (Online), July, 2020, pp.985-994. doi
  • H. Deng, Y. Wang, J. Luo and J. Hu, "Similitude Attentive Relation Network for Click-Through Rate Prediction", in Proc. of 2020 IEEE International Joint Conference on Neural Networks (IJCNN 2020), July, 2020. doi

2019 Journal Papers

  • Y. Tian, Q. Zhang, Z. Ren, F. Wu, P. Hao and J. Hu, "Multi-Scale Dialted Convolution Network Based Depth Estimation in Intelligent Transportation Systems", IEEE Access, Vol.7, pp.185179-185188, December, 2019. doi
  • W. Li, P. Liang and J. Hu, "An Autoencoder Based Piecewise Linear Model for Nonlinear Classification using Quasi-Linear Support Vector Machines", IEEJ Trans. on Electrical and Electronic Engineering, Vol.14, No.8, pp.1236-1243, August, 2019. doi
  • B. Zhou, W.Li and J.Hu, "A Coarse-to-Fine Two-step Method for Semi-Supervised Classification Using Quasi-Linear Laplacian SVM", IEEJ Trans. on Electrical and Electronic Engineering, Vol.14, No.3, pp.441-448, March, 2019. doi
  • P. Liang, W.Li, H.Tian and J.Hu, "One-Class Classification Using Support Vector Machine with Quasi-Linear Kernel", IEEJ Trans. on Electrical and Electronic Engineering, Vol.14, No.3, pp.449-456, March, 2019. doi
  • P. Liang, F. Zheng, W.Li and J.Hu, "Quasi-Linear SVM Classifier with Segmented Local Offsets for Imbalanced Data Classification", IEEJ Trans. on Electrical and Electronic Engineering, Vol.14, No.2, pp.288-296, Feb., 2019. doi

2019 Proceeding Papers

  • H. Zhu and J. Hu, "Air Quality Forecasting using SVR with Quasi-Linear Kernel", in Proc. of the 2019 International Conference on Computer, Information and Telecommunication Systems (CITS 2019) (Bejing), August, 2019, 126-130. doi
  • X. Yuan, W. Li, K. Lin and J. Hu, "A Deep Neural Network Based Hierarchical Multi-LabelClassifier for Protein Function Prediction", in Proc. of the 2019 International Conference on Computer, Information and Telecommunication Systems (CITS 2019) (Bejing), August, 2019, 131-135. doi
  • Y. Ren, W. Li and J. Hu, "A Semi-Supervised Classification Using Gated Linear Model", in Proc. of 2019 IEEE International Joint Conference on Neural Networks (IJCNN 2019) (Budapest), July, 2019. doi

2018 Journal Papers

  • P. Liang, W.Li and J.Hu, "Oversampling the Minority Class in a Multi-Linear Feature Space for Imbalanced Data Classification", IEEJ Trans. on Electrical and Electronic Engineering, Vol.13, No.10, pp.1483-1491, Oct., 2018. doi

2018 Proceeding Papers

  • P. Liang, W. Li, Y. Wang and J. Hu, "One-Class Classification using Quasi-Linear Support Vector Machine", in Proc. of IEEE Inter. Conference on Systems, Man and Cybernetics (SMC 2018) (Miyazaki), Oct., 2018, pp.658-663. doi
  • P. Liang, X. Yao and J. Hu, "A Metric Learning Method for Improving Neural Network Based Kernel Learning for SVM", in Proc. of IEEE Inter. Conference on Systems, Man and Cybernetics (SMC 2018) (Miyazaki), Oct., 2018, pp.1637-1642. doi
  • Y. Cui, Y.P. Sun and J. Hu, "A Convolutional AutoEncoder Method for Anomaly Detection on System Logs", in Proc. of IEEE Inter. Conference on Systems, Man and Cybernetics (SMC 2018) (Miyazaki), Oct., 2018, pp.3053-3058. doi
  • L.J.V. Miranda and J. Hu, "Feature Extraction using a Mutually-Competitive Autoencoder for Protein Function Prediction", in Proc. of IEEE Inter. Conference on Systems, Man and Cybernetics (SMC 2018) (Miyazaki), Oct., 2018, pp.1333-1338. doi
  • P. Liang, X. Yuan, W. Li and J. Hu, "An Segmented Local Offset Method for Imbalanced Data Classification Using Quasi-Linear Support Vector Machine", in Proc. of Inter. Conference on Pattern Recognition (ICPR 2018) (Beijing), August, 2018, pp.746-751. doi
  • Y.P. Sun, Y. Cui, J. Hu and W.J. Jia, "Relation Classification using Coarse And Fine-Grained Networks with SDP Supervised Key Words Selection", in Proc. of the 11th Inter. Conference on Knowledge Science, Engineering and Management (KSEM 2018) (Changchun), August, 2018, pp.514-521. doi
  • L.J.V. Miranda and J. Hu, "A Deep Learning Approach Based on Stacked Denoising Autoencoders for Protein Function Prediction", in Proc. of the 42th IEEE Inter. Conference on Computers, Software and Applications (COMPSAC 2018) (Tokyo), July, 2018, pp.480-485. doi

2017 Journal Papers

  • L.Wang, Y.Cheng, J.Hu, J. Liang and A.M.Dobai, "Nonlinear System Identification Using Quasi-ARX RBFN Models with a Parameter-Classified Scheme", Complexity, Vol.2017, Article ID 8197602, 12 Pages.
  • W.Li, B.Zhou, B.Chen and J.Hu, "A Geometry-Based Two-step Method for Nonlinear Classification Using Quasi-Linear Support Vector Machine", IEEJ Trans. on Electrical and Electronic Engineering, Vol.12, No.6, pp.883-890, Nov., 2017. doi
  • B.Zhou, W.Li and J.Hu, "A New Segmented Oversampling Method for Imbalanced Data Classification Using Quasi-Linear Support Vector Machine", IEEJ Trans. on Electrical and Electronic Engineering, Vol.12, No.6, pp.891-898, Nov., 2017. doi
  • W.Cao, A.Song and J.Hu, "Stacked Residual Recurrent Neural Network with Word Weight for Text Classification", IAENG International Journal of Computer Science, Vol.44, No.3, pp.277-284, Sept., 2017.
  • Z.Shi and J.Hu, "A Kernel Approach to Implementation of Local Linear Discriminant Analysis for Face Recognition", IEEJ Trans. on Electrical and Electronic Engineering, Vol.12, No.1, pp.60-70, Jan., 2017. doi

2017 Proceeding Papers

  • P. Liang, W. Li, D. Liu and J. Hu, "Large-Scale Image Classification Using Fast SVM with Deep Quasi-Linear Kernel", in Proc. of 2017 IEEE International Joint Conference on Neural Networks (IJCNN'2017) (Anchorage), May, 2017, pp1064-1071. doi
  • W. Li, B. Chen, B. Zhou and J. Hu, "A Mixture of Multiple Linear Classifiers with Sample Weight and Manifold Regularization", in Proc. of 2017 IEEE International Joint Conference on Neural Networks (IJCNN'2017) (Anchorage), May, 2017, pp.3747-3752. doi
  • W. Li and J. Hu, "A Multilayer Gated Bilinear Classifier: from Optimizing a Deep Rectified Network to a Support Vector Machine", in Proc. of 2017 IEEE International Joint Conference on Neural Networks (IJCNN'2017) (Anchorage), May, 2017, pp.140-146. doi
  • W. Li, P. Liang, X. Yuan and J. Hu, "Non-Local Information for a Mixture of Multiple Linear Classifiers", in Proc. of 2017 IEEE International Joint Conference on Neural Networks (IJCNN'2017) (Anchorage), May, 2017, pp.3741-3746. doi
  • W. Wang, Y. Zhang and J. Hu, "Distance Metric Learning with Eigenvalue Fine Tuning", in Proc. of 2017 IEEE International Joint Conference on Neural Networks (IJCNN'2017) (Anchorage), May, 2017, pp.502-509. doi

2016 Journal Papers

  • W. Li, B. Zhou, B. Chen and J. Hu, "A Deep Neural Network Based Quasi-linear Kernel for Support Vector Machines", IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E99-A, No.12, pp.2558-2565, Dec., 2016. doi
  • J. Zhang and J. Hu, "Surface Reconstruction of Renal Corpuscle from Microscope Renal Biopsy Image Sequence", IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E99-A, No.12, pp.2539-2546, Dec., 2016. doi
  • I. Sutrisno, M.A. Jami'in, J. Hu and M.H. Marhaban, "A Self-Organizing Quasi-Linear ARX RBFN Model for Nonlinear Dynamical Systems Identification", SICE Journal of Control, Measurement, and System Integration, Vol.9, No.2, pp.70-77, March, 2016. doi
  • M.A. Jami'in, I. Sutrisno, J. Hu, N.B. Mariun and M.H. Marhaban, "Quasi-ARX Neural Network Based Adaptive Predictive Control for Nonlinear Systems", IEEJ Trans. on Electrical and Electronic Engineering, Vol.11, No.1, pp.83-90, Jan., 2016. doi

2016 Proceeding Papers

  • W. Li, J. Hu and B. Chen, "A Deep Quasi-Linear Kernel Composition Method for Support Vector Machine", in Proc. of 2016 IEEE International Joint Conference on Neural Networks (IJCNN'2016) (Vancouver), July, 2016, pp.1639-1645. doi
  • W. Li, B. Zhou and J. Hu, "A Kernel Level Composition of Multiple Local Classifiers for Nonlinear Classification", in Proc. of 2016 IEEE International Joint Conference on Neural Networks (IJCNN'2016) (Vancouver), July, 2016, pp.3845-3850. doi
  • M.A. Jami'in, J. Hu and E. Julianto, "A Lyapunov Based Switching Control to Track Maximum Power Point of WECS", in Proc. of 2016 IEEE International Joint Conference on Neural Networks (IJCNN'2016) (Vancouver), July, 2016, pp.3883-3888. doi
  • B. Chen, W. Li, Y. Zhang and J. Hu, "Enhancing Multi-label Classification Based on Local Label Constraints and Classifier Chains", in Proc. of 2016 IEEE International Joint Conference on Neural Networks (IJCNN'2016) (Vancouver), July, 2016, pp.1458-1463. doi
  • J. Zhang and J. Hu, "A Novel Registration Method based on Coevolutionary Strategy", in Proc. of 2016 IEEE Congress on Evolutionary Computation (CEC'2016) (Vancouver), July, 2016, pp.2375-2380. doi
  • I. Sutrisno, M.A. Jamiin, J. Hu and N. Mariun, "Application of Self Organizing Quasi-ARX RBFN for Rotor Speed Tracking Control of a Wind Turbine", in Proc. 21th International Symposium on Artificial Life and Robotics (AROB 21th'2016) (Bepu), Jan., 2016.

2015 Journal Papers

  • M.A. Jami'in, I. Sutrisno and J. Hu, "Maximum Power Tracking Control for a Wind Energy Conversion System Based on a Quasi-ARX Neural Network Model", IEEJ Trans. on Electrical and Electronic Engineering, Vol.10, No.4, pp.368-375, July, 2015. doi
  • J. Zhang and J. Hu, "Context-based Segmentation of Renal Corpuscle from Microscope Renal Biopsy Image Sequence", IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E98-A, No.5, pp.1114-1121, May, 2015. doi

2015 Proceeding Papers

  • I. Sutrisno, M.A. Jami'in, J. Hu and M.H. Marhaban, "Self-Organizing Quasi-Linear ARX RBFN Modeling for Identification and Control of Nonlinear Systems", in Proc. of 2015 SICE Annual Conference (SICE'2015) (Hangzhou), pp.788-793, July, 2015. doi
  • B. Zhou, D. Fu, C. Dong and J. Hu, "A Tranductive SVM with Quasi-linear Kernel Based on Cluster Assumption for Semi-Supervised Classification", in Proc. of 2015 IEEE International Joint Conference on Neural Networks (IJCNN'2015) (Killarney), July, 2015. doi
  • W. Li and J. Hu, "Geometric Approach of Quasi-linear Kernel Composition for Support Vector Machine", in Proc. of 2015 IEEE International Joint Conference on Neural Networks (IJCNN'2015) (Killarney), July, 2015. doi
  • D. Fu, B. Zhou and J. Hu, "Improving SVM Based Multi-label Classification by Using Label Relationship", in Proc. of 2015 IEEE International Joint Conference on Neural Networks (IJCNN'2015) (Killarney), July, 2015. doi
  • C. Dong, B. Zhou and J. Hu, "A Hierarchical SVM Based Multiclass Classification by Using Similarity Clutering", in Proc. of 2015 IEEE International Joint Conference on Neural Networks (IJCNN'2015) (Killarney), July, 2015. doi
  • M.A. Jamiin, I. Sutrisno and J. Hu, "The State-Dynamic-Error-Based Switching Control under Quasi-ARX Neural Network Model", in Proc. 20th International Symposium on Artificial Life and Robotics (AROB 20th'2015) (Bepu), Jan., 2015, pp.787-792.

2014 Journal Papers

  • I. Sutrisno, C. Che and J. Hu, "An Improved Adaptive Switching Control Based on Quasi-ARX Neural Network for Nonlinear Systems", Artificial Life and Robotics, Vol.19, No.4, pp.347-353, Oct., 2014.
  • I. Sutrisno, M.A. Jami'in and J. Hu, "An Improved Elman Neural Network Controller Based on Quasi-ARX Neural Network for Nonlinear Systems", IEEJ Trans. on Electrical and Electronic Engineering, Vol.9, No.5, pp.494-501, September, 2014. doi
  • B. Zhou, B. Chen and J. Hu, "Quasi-linear Support Vector Machine for Nonlinear Classification", IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E97-A, No.7, July, pp.1587-1594, 2014. doi
  • I. Sutrisno, M.A. Jami'in and J. Hu, "Modified Fuzzy Adaptive Controller Applied to Nonlinear Systems Modeled under Quasi-ARX Neural Netwrok", Artificial Life and Robotics, Vol.19, No.1, pp.22-26, February, 2014.

2014 Proceeding Papers

  • M.A. Jamiin, I. Sutrisno, J. Hu, N.B. Mariun and M.H. Marhaban, "An Adaptive Predictive Control Based on a Quasi-ARX Neural Network Model", in Proc. of 13th Inter. Conference on Control, Automation, Robotics and Vision (ICARCV2014) (Singapore), Dec., 2014, pp.253-258. doi
  • J. Lin, M. Song and J. Hu, "An SMO Approach to Fast SVM for Classification of Large Scale Data", in Proc. of 2014 International Conference on IT Convergence and Security (ICITCS'2014) (Beijin), Oct., 2014. doi
  • I. Sutrisno, M.A. Jamiin, and J. Hu, "Nonlinear Model-Predictive Control Based on Quasi-Radial-Basis-Function-Neural-Network", in Proc. of 8th Inter. Conference on Mathematical Modelling and Computer Simulation (AMS2014) (Taipei), Sept., 2014, pp.104-109. doi
  • P. Liang, Y. Zhang, K. Lin and J. Hu, "A Fast Sequence Assembly Method Based on Compressed Data Structures", in Proc. of 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC2014) (Chicago), Aug., 2014, pp.326-329. doi
  • Y. Luo, S. Huang, and J. Hu, "A Niching Two-layered Differential Evolution with Self-adaptive Control Parameters", in Proc. of 2014 IEEE Congress on Evolutionary Computation (CEC'2014) (Beijing), July, 2014, pp.1405-1412. doi
  • C. Hu, B. Zhou, and J. Hu, "Fast Support Vector Data Description Training Using Edge Detection on Large Datasets", in Proc. of 2014 IEEE International Joint Conference on Neural Networks (IJCNN'2014) (Beijing), July, 2014, pp.2176-2182. (Best Student Paper Award - Finalist) doi
  • W. Dou, and J. Hu, "A Half-Split Grid Clustering Algorithm by Simulating Cell Division", in Proc. of 2014 IEEE International Joint Conference on Neural Networks (IJCNN'2014) (Beijing), July, 2014, pp.2183-2189. doi
  • B. Zhou, C. Hu, B. Chen and J. Hu, "A Transductive Support Vector Machine with Adjustable Quasi-linear Kernel for Semi-supervised Data Classification", in Proc. of 2014 IEEE International Joint Conference on Neural Networks (IJCNN'2014) (Beijing), July, 2014, pp.1409-1415. doi
  • Y. Lin, Y. Fu, and J. Hu, "Support Vector Machine with SOM-based Quasi-linear Kernel for Nonlinear Classification", in Proc. of 2014 IEEE International Joint Conference on Neural Networks (IJCNN'2014) (Beijing), July, 2014, pp.3783-3789. doi
  • M.A. Jami'in, I. Sutrisno, and J. Hu, "Nonlinear Adaptive Control for Wind Energy Conversion Systems Based on Quasi-ARX Neural Network Model", in Proc. of the International MultiConference of Engineers and Computer Scientists (IMECS'2014) (Hongkong), Vol.I, March, 2014, pp.313-318.
  • I. Sutrisno, C. Che and J. Hu, "Quasi-ARX NN Based Adaptive Control Using Improved Fuzzy Switching Mechanism for Nonlinear Systems", in Proc. 19th International Symposium on Artificial Life and Robotics (AROB 19th'2014) (Bepu), Jan., 2014, pp.697-702.

2013 Journal Papers

  • Z. Shi and J. Hu, "A Modified Pulse Coupled Neural Network with Anisotropic Synaptic Weigh Matrix for Image Edge Detection", IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E96-A, No.6, pp.1460-1467, June, 2013. doi
  • B. Li, Q. Wang and J. Hu, "Fast SVM Training Using Edge Detection on Very Large Datasets", IEEJ Trans. on Electrical and Electronic Engineering, Vol.8, No.3, pp.229-237, May, 2013. doi
  • B. Li, Q. Wang and J. Hu, "Multi-SVM Classifier Systems with Piecewise Interpolation", IEEJ Trans. on Electrical and Electronic Engineering, Vol.8, No.2, pp.132-138, March, 2013. doi
  • Y. Lin, W. Shih and J. Hu, "Development of Stock Evaluation System Based on Quasi-Linear Regression Model", International Journal of Electronic Business Management, Vol.11, No.1, pp.23-32, March, 2013.

2013 Proceeding Papers

  • I. Sutrisno, M.A. Jami'in and J. Hu, "Implementation of Lyapunov Learning Algorithm for Fuzzy Switching Adaptive Controller Modeled Under Quasi-ARX Neural Network", in Proc. of the 2nd International Conference on Measurement, Information and Control (ICMIC'2013) (Harbin), Aug., 2013, pp.762-766. doi
  • M.A. Jami'in, I. Sutrisno and J. Hu, "Deep Searching for Model Parameters of Linear Time Invariant (LTI) system by Using Quasi-ARX Neural Network", in Proc. of 2013 IEEE International Joint Conference on Neural Networks (IJCNN'2013) (Dallas), Aug., 2013, pp.2758-2762. doi
  • Y. Lin, H. Guo and J. Hu, "A SVM-based Approach for Stock Market Trend Prediction", in Proc. of 2013 IEEE International Joint Conference on Neural Networks (IJCNN'2013) (Dallas), Aug., 2013, pp.237-242. doi
  • B. Chen, X. Hong, L. Duan and J. Hu, "Improving Multi-label Classification Performance by Label Constraints", in Proc. of 2013 IEEE International Joint Conference on Neural Networks (IJCNN'2013) (Dallas), Aug., 2013, pp.1103-1107. doi
  • B. Zhou, C. Yang, H. Guo and J. Hu, "A Quasi-linear SVM Combined with Assembled SMOTE for Imbalanced Data Classification", in Proc. of 2013 IEEE International Joint Conference on Neural Networks (IJCNN'2013) (Dallas), Aug., 2013, pp.2351-2357. doi

2012 Journal Papers

  • H. Sun, H. Guo, J. Hu, and K. Zhu, "Comparative Study on Economic Contribution Rate of Education of China and Foreign Contries Based on Softcomputing Method", Applied Soft Computing, Vol.12, No.8, pp.2106-2113, August, 2012.
  • H. Guo, J. Hu, S. Yu. H. Sun and Y. Chen, "Computing of the Contribution Rate of Scientific and Technological Progress to Economic Growth in Chinese Regions ", Expert Systems with Applications, Vol.39, No.10, pp.8514-8521, August, 2012.
  • L. Wang, Y. Cheng and J. Hu, "Stabilizing Switching Control for Nonlinear System Based on Quasi-ARX Model ", IEEJ Trans. on Electrical and Electronic Engineering, Vol.7, No.4, pp.390-396, July, 2012. doi
  • Y. Cheng, L. Wang and J. Hu, "Identification of Quasi-ARX Neurofuzzy Model with an SVR and GA Approach", IEICE Trans on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E95-A, No.5, pp.876-883, May, 2012. doi
  • B. Chen and J. Hu, "Hierarchical Multi-label Classification Based on Over-sampling and Hierarchy Constraint for Gene Function Prediction", IEEJ Trans. on Electrical and Electronic Engineering, Vol.7, No.2, pp.183-189, March, 2012. doi
  • L. Wang, Y. Cheng and J. Hu, "A Quasi-ARX Model for Multivariable Decoupling Control of Nonlinear MIMO System", Mathematical Problems in Engineering, Vol.2012, Article ID 570498, 13 pages, doi:10.1155/2012/570498, 2012. doi

2012 Proceeding Papers

  • W. Dou and J. Hu, "Automated Web Data Mining Using Semantic Analysis", in LNCS 7713, Advanced Data Mining and Application (Proc. of ADMA'2012 (Nanjing)), Dec., 2012, pp.539-551.
  • M.A. Jami'in, I. Sutrisno and J. Hu, "Lyapunov Learning Algorithm for Quasi-ARX Neural Network to Identification of Nonlinear Dynamical System", in Proc. of IEEE International Conference on Systems, Man, and Cybernetics (SMC'2012) (Seoul), Oct., 2012, pp.3141-3146. doi
  • I. Sutrisno, M.A. Jami'in and J. Hu, "Neural Predictive Controller of Nonlinear Systems Based on Quasi-ARX Neural Network", in Proc. of the 18th International Conference on Automation and Computing (ICAC12) (Leicestershire), Sept., 2012, pp.83-88.
  • Y. Cheng and J. Hu, "Nonlinear System Identification Based on SVR with Quasi-linear Kernel", in Proc of 2012 IEEE International Joint Conference on Neural Networks (IJCNN'12)(Brisbane), June, 2012, pp.2368-2375. doi
  • Z. Shi and J. Hu, "Local Linear Discriminant Analysis with Composite Kernel for Face Recognition", in Proc of 2012 IEEE International Joint Conference on Neural Networks (IJCNN'12)(Brisbane), June, 2012, pp.166-170. doi
  • B. Chen, L. Duan and J. Hu, "Composite Kernel Based SVM for Hierarchical Multi-label Gene Function Classification", in Proc of 2012 IEEE International Joint Conference on Neural Networks (IJCNN'12)(Brisbane), June, 2012, pp1380-1385. doi

2011 Journal Papers

  • Y. Chen and J. Hu, "Accurate Reconstruction for DNA Sequencing by Hybridization Based on A Constructive Heuristic", IEEE/ACM Trans. on Computational Biology and Bioinformatics, Vol.8, No.4, pp.1134-1140, July/Aug., 2011. doi
  • Y. Cheng, L. Wang M. Yu and J. Hu, "An Efficient Identification Scheme for a Nonlinear Polynomial NARX Model", Artificial Life and Robotics, Vol.16, No.1, pp.70-73, June 2011.
  • Y. Cheng, L. Wang and J. Hu, "A Two-step Scheme for Polynomial NARX Model Identification Based on MOEA with Pre-screening Process", IEEJ Trans. on Electrical and Electronic Engineering, Vol.6, No.3, pp.253-259, May 2011. doi
  • J. Zhang, J. Hu and H. Zhu, "Contour Extraction of Glomeruli by Using Genetic Algorithm for Edge Patching", IEEJ Trans. on Electrical and Electronic Engineering, Vol.6, No.3, pp.229-235, May 2011. doi
  • Y. Cheng, L. Wang and J. Hu, "Quasi-ARX Wavelet Network for SVR Based Nonlinear System Identification", Nonlinear Theory and its Applications (NOLTA), IEICE, Vol.2, No.2, pp.165-179, April 2011. doi
  • B. Li, Q. Wang and J. Hu, "Feature Subset Selection: A Correlation-Based SVM Filter Approach", IEEJ Trans. on Electrical and Electronic Engineering, Vol.6, No.2, pp.173-179, 2011. doi

2011 Proceeding Papers

  • Y. Cheng, L. Wang, and J. Hu, "A Quasi-linear Approach for Microaary Missing Value Imputation", in Proc. of 18th International Conference on Neural Information Processing (ICONIP'11)(Shanghai), Nov., 2011, pp.233-240.
  • Y. Cheng, L. Wang, J. Zeng and J. Hu, "Identification of Quasi-ARX Neurofuzzy Model by Using SVR-based Approach with Input Selection", in Proc of 2011 IEEE International Conference on Systems, Man and Cybernetics (SMC'11)(Anchorage), Oct., 2011, pp.1585-1590.
  • L. Wang, Y. Cheng and J. Hu, "Multivariable Self-Tuning Control for Nonlinear MIMO System Using Quasi-ARX RBFN Model", in Proc. of the 30th Chinese Control Conference (CCC'2011) (Yantai), July, 2011, pp.3772-3776.
  • B. Chen, J. Hu and L. Duan, "Niching EDA Based on Fitness Sharing for Off-latice Protein Folding Model", in Proc 2011 International Conference on Fuzzy Systems and Neural Computing (FSNC'2011)(Hongkong), Feb., 2011, pp.128-131.
  • L. Wang, Y. Cheng and J. Hu, "Adaptive Switching Control Based on Quasi-ARX RBFN Model", in Proc. 2011 International Conference on Computers, Communications, Control and Automation (CCCA'2011)(Hongkong), Feb., 2011, pp.76-79.
  • Y. Cheng, M. Yu, L. Wang and J. Hu, "An Efficient Identification Scheme for Nonlinear Polynomial NARX Model", in Proc. 16th International Symposium on Artificial Life and Robotics (AROB 16th'11) (Bepu), Jan., 2011, pp.499-502.

2010 Journal Papers

  • B. Chen and J. Hu, "An Adaptive Niching EDA with Balance Searching Based on Clustering Analysis", IEICE Trans on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E93-A, No.10, Oct. 2010. doi
  • B. Chen, W. Gu and J. Hu, "An Improved Multi-label Classification Method and Its Application to Functional Genomics", Int. J. Computational Bilogy and Drug Design, Vol.3, No.2, pp.133-145, 2010.
  • L. Wang, Y. Cheng and J. Hu, "A Quasi-ARX Neural Network with Switching Mechanism to Adaptive Control of Nonlinear Systems", SICE Journal of Control, Measurement, and System Integration, Vol.3, No.4, pp.246-252, July 2010. doi
  • B. Chen and J. Hu, "A Hybrid EDA for Protein Folding Based on HP Model", IEEJ Trans. on Electrical and Electronic Engineering, Vol.5, No.4, pp.459-466, July 2010. doi
  • J. Zhang and J. Hu, "Color Quantization Based on Hierarchical Frequency Sensitive Competitive Learning", Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.14, No.4, pp.375-381, May 2010.
  • B. Chen, L. Ma and J. Hu, "An Improved Multi-label Classification Method Based on SVM with Delicate Decision Boundary", International Journal of Innovative Computing, Information and Control, Vol.6, No.4, pp.1605-1614, April 2010.
  • J. Zhang, J. Hu and H. Zhu, "Extraction of Glomeruli Using a Canny Operator with a Feedback Strategy", JAMIT Medical Imaging Technology, Vol.28. No.2, pp.127-134, March 2010.

2010 Proceeding Papers

  • B. Chen F. Sun and J. Hu, "Local Linear Multi-SVM Method for Gene Function Classification", in Proc. of the World Congress on Nature and Biologically Inspired Computing (NaBIC2010)(Kitakyushu), Dec., 2010, pp.183-188.
  • Z. Shi and J. Hu, "An Adaptive Switching Median Filter with Anisotropic Linking PCNN Noise Detection for Salt and Pepper Noise Reduction", in Proc. of the World Congress on Nature and Biologically Inspired Computing (NaBIC2010)(Kitakyushu), Dec., 2010, pp.240-245.
  • B. Chen and J. Hu, "Hierarchical Multi-label Classifiication Incorporating Prior Information for Gene Function Predicition", in Proc. of the 12th International Conference on Intelligent Systems Design and Applications (ISDA'10)(Cairo), Nov., 2010, pp.231-236.
  • Z. Shi and J. Hu, "Image Edge Detection Method Based on a Simplified PCNN Model with Anisotropic Linking Mechanism", in Proc. of the 12th International Conference on Intelligent Systems Design and Applications (ISDA'10)(Cairo), Nov., 2010, pp.324-329.
  • L. Wang, Y. Cheng and J. Hu, "Nonlinear Adaptive Control Using Support Vector Regression Based on Improved Quasi-ARX Model", in Proc. of 2010 International Conference on Modeling, Simulation and Control (ICMSC'10) (Cairo), Nov., 2010, pp.412-416.
  • Y. Cheng, L. Wang and J. Hu, "Quasi-ARX Wavelet Networks for Nonlinear System Identification", in Proc. of 2010 International Conference on Modeling, Simulation and Control (ICMSC'10) (Cairo), Nov., 2010, pp.407-411.
  • W. Gu, B. Chen and J. Hu, "Combining Binary-SVM and Pairwise Label Constraints for Multi-label Classification", in Proc of 2010 IEEE International Conference on Systems, Man and Cybernetics (SMC'10)(Istanbul), Oct., 2010, pp.4176-4181.
  • J. Zhang and J. Hu, "A Hierarchical Clustering Method for Color Quantization", in Proc. of 2010 International Conference on Pattern Recognition (ICPR2010) (Istanbul), Aug., 2010, pp.786-789.
  • L. Wang, Y.  Cheng and J. Hu, "Nonlinear Adaptive Control Using a Fuzzy Switching Mechanism Based on Improved Quasi-ARX Neural Network", in Proc of 2010 IEEE International Joint Conference on Neural Networks (IJCNN'10)(Barcelona), July 2010, pp.3078-3084.
  • G. Sun, J. Hu and G. Wu, "A Novel Frequency Band Selection Method for Common Spatial Pattern in Motor Imagery Based Brain Computer Interface", in Proc of 2010 IEEE International Joint Conference on Neural Networks (IJCNN'10)(Barcelona), July 2010, pp.335-340.
  • B. Chen, W. Gu and J. Hu, "An Improved Multi-label Classification Based on Label Ranking and Delicate Boundary SVM", in Proc of 2010 IEEE International Joint Conference on Neural Networks (IJCNN'10)(Barcelona), July 2010, pp.786-790.
  • B. Chen and J. Hu, "An Adaptive Niching EDA Based on Clustering Analysis", in Proc. of 2010 IEEE Congress on Evolutionary Computation (CEC'10) (Barcelona), July 2010, pp.858-860.
  • Y. Chen and J. Hu, "eSBH: An Accurate Constructive Heuristic Algorithm for DNA Sequencing By Hybridization", in Proc. of the 10th IEEE International Conference on Bioinformatics and Bioengineering (IEEE-BIBE 2010)(Philadelphia), May 2010, pp.124-129.
  • J. Zhang and J. Hu, "Variable Structure Neural Network for Adaptive Color Clustering", in Proc. of the 7th IASTED International Conference Signal Processing, Pattern Recognition and Applications (SPPRA 2010) (Innsbruck), Feb. 2010, pp.248-252.
  • L. Wang, Y. Cheng and J. Hu, "Quasi-ARX neural network and its application to adaptive control of nonlinear systems", in Proc. 15th International Symposium on Artificial Life and Robotics (AROB 15th'10) (Bepu), 2, 2010, pp. 577-580.

2009 Journal Papers

  • Q. Wang, B. Li and J. Hu, "Human Resource Selection Based on Performance Classification Using Weighted Support Vector Machine", Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.13, No.4, pp.407-417,  2009.
  • J. Zhang and J. Hu, "Automatic Segmentation Technique for Color Images", ICGST International Journal on Graphics, Vision and Image Processing (GVIP), Vol.9, No.3, pp.41-49, June, 2009.
  • J. Zhang and J. Hu, "Renal Biopsy Image Segmentation Based on 2-D Otsu Method with Histogram Analysis", JAMIT Medical Imaging Technology, Vol.27, No.3, pp.185-192, May, 2009.
  • J. Zhang, Q. Zhang and J. Hu, "RGB Color Centroids Segmentation (CCS) for Face Detection", ICGST International Journal on Graphics, Vision and Image Processing (GVIP), Vol.9, No.2, pp.1-9, April, 2009.
  • B. Chen, J. Hu, L. Duan and Y. Gu, "Network Administrator Assistance System Based on Fuzzy C-means Analysis", Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.13, No.2, March, pp.91-96, 2009.

2009 Proceeding Papers

  • B. Chen and J. Hu, "A Novel Clustering Based Niching EDA for Protein Folding",  in Proc. of World Congress on Nature and Biologically Inspired Computing (NaBIC 2009) (India), 12, 2009, pp.748-753.
  • Y. Cheng, L. Wang and J. Hu, "A Two-step Method for Nonlinear Polynomial Model Identification Based on Evolutionary Optimization", in Proc. of World Congress on Nature and Biologically Inspired Computing (NaBIC 2009) (India), 12, 2009, pp.613-618.
  • L. Wang, Y. Cheng and J. Hu, "Adaptive Control for Nonlinear Systems Based on Quasi-ARX Neural Network", in Proc. of World Congress on Nature and Biologically Inspired Computing (NaBIC 2009) (India), 12, 2009, pp.1548-1551.
  • Q. Wang, B. Li and J. Hu, "Feature Selection for Human Resource Selection Based on Affinity Propagation and SVM Sensitivity", in Proc. of World Congress on Nature and Biologically Inspired Computing (NaBIC 2009) (India), 12, 2009, pp.31-36.
  • B. Zhou and J. Hu, "A Dynamic Pattern Recognition Approach Based on Neural Network for Stock Time-Series", in Proc. of World Congress on Nature and Biologically Inspired Computing (NaBIC 2009) (India), 12, 2009, pp.1552-1555.
  • L. Wang and J. Hu, "An Improvement of Quasi-ARX Predictor to Control of Nonlinear Systems Using Nonlinear PCA Network", in Proc. of ICROS-SICE International Joint Conference 2009 (Fukuoka), 8, 2009, pp.5095-5099.
  • B. Chen, L. Li and J. Hu, "An Improved Backtracking Method for EDAs Based Protein Folding", in Proc. of ICROS-SICE International Joint Conference 2009 (Fukuoka), 8, 2009, pp.4669-4673.
  • Y. Cheng, Y. Jin and  J. Hu, "Adaptive Epsilon Non-dominated Sorting Multi-objective Evolutionary Optimization and Its Application in Shortest Path Problem", in Proc. of ICROS-SICE International Joint Conference 2009 (Fukuoka), 8, 2009, pp.2545-2549.
  • W. Dou, J. Hu and G. Wu, "Interesting Rules Mining with Deductive Method", in Proc. of ICROS-SICE International Joint Conference 2009 (Fukuoka), 8, 2009, pp.142-146.
  • J. Zhang and J. Hu, "An Automatic Segmentation Technique for Color Images Based on SOFM Neural Network", in Proc. of International Joint Conference on Neural Networks (Atlanta), June 2009, pp.3528-3533.
  • B. Li, Q. Wang and J. Hu, "A Fast SVM Training Method for Very Large Datasets", in Proc. of International Joint Conference on Neural Networks (Atlanta), June 2009, pp.1784-1789.
  • J. Ma, J. Zhang and J. Hu, "Glomerulus Extraction by Using Genetic Algorithm for Edge Patching", in Proc. 2009 IEEE Congress on Evolutionary Computation (CEC'09) (Trondheim), 5, 2009, pp.2474-2479.
  • B. Chen, L. Li and J. Hu, "A Novel EDAs Based Method for HP Model Protein Folding", in Proc. 2009 IEEE Congress on Evolutionary Computation (CEC'09) (Trondheim), 5, 2009, pp.309-315.
  • J. Zhang and J. Hu, "Curvilinear Thresholding Method for Noisy Images Based on 2D Histogram", in Proc. of the 2008 International Conference on Robotics and Biomimetics (Bangkok), Feb., 2009, pp.1014-1019.

2008 Journal Papers

  • B. Li, J. Hu and K. Hirasawa, "Support Vector Machine Classifier with WHM Offset for Unbalanced Data",  Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.12, No.1, pp.94-101, 2008.
  • T. Sasakawa, J. Hu and K. Hirasawa, "A Brainlike Learning  System with Supervised, Unsupervised, and Reinforcement Learning", Electrical Engineering in Japan, Vol.162, No.1, pp.32-39, 2008.

 

2008 Proceeding Papers

  • J. Zhang and J. Hu, "Curvilinear Thresholding Method for Noisy Images Based on 2D Histogram", in Proc. of the 2008 International Conference on Robotics and Biomimetics (Bangkok), Feb., 2009, pp.1014-1019.
  • Y. Xu, Q. Wang and J. Hu, "An Improved Discrete Particle Swarm Optimization Based on Cooperative Swarms", in Proc. of the 2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'08) (Sydney), Vol.2, 79-82, Dec. 2008 .
  • J. Zhang and J. Hu, "Nuclei Extraction Based on Multi-channel Information", in Proc of Digital Image Computing: Techniques and Application (Canberra), Dec., 2008, pp.59-64.
  • J. Zhang and J. Hu, "Image Segmentation Based on 2D Otsu Method with Histogram Analysis", in Proc of 2008 International Conference on Computer Science and Software Engineering (Wuhan), 2008, pp.105-108.
  • J. Zhang and J. Hu, "Glomeruli Segmentation Based on Neural Network with Fault Tolerance", in Proc. of 2008 International  Symposium on Computational Intelligence and Design (Wuhan),  Oct. 2008, pp.401-404.
  • J. Zhang and J. Hu, "Glomerulus Extraction by Optimizing the  Fitting Curve", in Proc. of 2008 International  Symposium on Computational Intelligence and Design (Wu Han), Oct. 2008, pp.169-172.
  • B. Chen, J. Hu, L. Duan and Y. Gu, "Network Administrator Assistance System Based on on Fuzzy C-Means Analysis", in Proc. of  the 3rd International Symposium on Computational Intelligence and Industrial Applications (Dali), 11, 49-55, 2008 .
  • B. Chen, L. Ma and J. Hu, "A New SVM Based Method for Solving Multi-Label Classification Problem", in Proc. of  the 3rd International Symposium on Computational Intelligence and Industrial Applications (Dali), 11, 325-334, 2008 .
  • Q. Wang, J. Hu and Y. Zhou, "Weighted Support Vector Machine with Combination Weighting Method for Human Resource Selection", in Proc. of  the 3rd International Symposium on Computational Intelligence and Industrial Applications (Dali), 11, 405-413, 2008 .
  • J. Hu and B. Chen, "A New Method for Identifying Nonlinear Polynomial Model Using Genetic Algorithm", in Proc. of  the 3rd International Symposium on Computational Intelligence and Industrial Applications (Dali), 11, 75-84, 2008 .
  • Q. Wang, B. Li and J. Hu, "Human Resource Selection Based on Performance Classification Using Weighted Support Vector Machine",  in Prod. of Joint 4th International Conference on Soft Computing  and Intelligent Systems and 9th International Symposium on Advanced Intelligent Systems, 9,  1837-1842, 2008 .
  • W. Dou, J. Hu, K. Hirasawa and G. Wu, "Quick Response Data Mining Model Using Genetic Algorithm", in Proc. of SICE Annual Conference, 8, 1214-1219, 2008.
  • B. Li, L. Ma, J. Hu and K. Hirasawa, "Gene Classification Using An Improved SVM Classifier with Soft Decision Boundary", in Proc. of SICE Annual Conference, 8, 2476-2480, 2008 .
  • B. Li, J. Hu and Hirasawa, "Financial Time Series Prediction Using a Support Vector Regression Network",  in Proc. of  International Joint Conference on Neural Networks (IJCNN2008) (Hongkong), 6, 2008, pp.622-628.
  • W. Dou, J. Hu, K. Hirasawa and G. Wu, "Distributed Multi-Relational Data Mining Based on Genetic Algorithm", in Proc of  2008 IEEE Congress on Evolutionary Computation (CEC2008) (Hongkong), 6, 2008, pp.744-750.
  • Y. Chen, J. Hu, K. Hirasawa and S. Yu, "Solving Deceptive Problems Using A Genetic Algorithm with Reserve Selection", in Proc of  2008 IEEE Congress on Evolutionary Computation (CEC2008) (Hongkong), 6, 2008, pp.884-889.
  • Y. Chen, J. Hu, K. Hirasawa and S. Yu, "Multiple Sequence Alignment Based on Genetic Algorithms with Reserve Selection", in Proc. of 2008 IEEE International Conference on Networking, Sensing and Control (ICNSC2008) (Sanya), 4, 2008, pp1512-1516.
  • B. Li,  J. Hu and K. Hirasawa, "An Improved Support Vector Machine with Soft Decision-Making Boundary", in Proc. of 2008 the IASTED  International Conference on Artificial Intelligence and Applications (AIA 2008) (Innsbruck),  2, 2008,  pp.40-45.

Journal Papers before 2008

  • 笹川・古月・平澤, "教師あり学習・教師なし学習・強化学習を複合したbrain- like学習システム", 電気学会論文誌C, Vol.126, No.9, 1165-1172, 2006.
  • 笹川・古月・平澤, "自己組織化機能局在型ニューラルネットワーク", 計測自動制御学会論文集, Vol.41, No.1, pp.67-74, 2005.
  • 古月・平澤, "非線形システムの制御のためのニューラルネットワーク予測モデル", 計測自動制御学会論文集, Vol.39, No.2, pp.168-175, 2003.
  • J.Hu, K.Kumamaru and K.Hirasawa, " A Quasi-ARMAX Approach to the Modeling of Nonlinear Systems ", International Journal of Control, Vol.74, No.18, pp.1754-1766, 2001.
  • J.Hu, K.Hirasawa and Q.Xiong, " Overlapped Multi-Neural-Network and Its Training Algorithm ", IEEJ Trans. on Electronics, Information and Systems, Vol.121, No.12, 1949-1956, 2001.
  • J.Hu, K.Hirasawa and K.Kumamaru, " A Homotopy Approach to Improving PEM Identification of ARMAX Model ", Automatica, Vol.37, No.9, pp.1323-1334, 2001.
  • J.Hu, K.Kumamaru and K.Hirasawa, "A Neurofuzzy Approach to Fault Detection of Nonlinear Systems ",  Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.3, No.6, pp.524-531,1999.
  • J.Hu, K.Hirasawa, J.Murata, C.Jin and T.Mtsuoka, " A Probabilistic Learning Network Based Robust Control Scheme for Nonlinear Systems ",  Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.3, No.6, pp.485-490,1999.
  • J.Hu, K.Hirasawa and K.Kumamaru, " A Neurofuzzy-Based Adaptive Predictor for Control of Nonlinear Systems ", Trans. of the Society of Instrument and Control Engineers, Vol.35, No.8, pp.1060-1068,1999.
  • J.Hu, K.Hirasawa and K.Kumamaru, " LimNet -- Flexible Learning Network Containing Linear Properties ", Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.3, No.4, pp.303-311,1999.
  • J.Hu and K.Hirasawa, "A Homotopy Approach to Identification of ARMAX Systems", IEEJ Trans. on Electronics, Information and Systems, Vol.119-C, No.2, pp.206-211, 1999.
  • J.Hu, K.Kumamaru, K.Inoue and K.Hirasawa, " KDI-Based Robust Fault Detection in Presence of Nonlinear Undermodeling", Trans. of the Society of Instrument and Control Engineers, Vol.35, No.2, pp.200-207,1999
  • J.Hu, K.Hirasawa and J.Murata, " RasID -- Random Search for Neural Networks Training ", Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.2, No.4, pp.134-141, 1998.
  • K.Hirasawa, J.Hu and J.Murata, " Computing Higher Order Derivatives in Universal Learning Networks ", Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.2, No.2, pp.47-53, 1998.
  • J.Hu, K.Kumamaru, K.Inoue and K.Hirasawa, " A Hybrid Quasi-ARMAX Modeling Scheme for Identification of Nonlinear Systems ", Trans. of the Society of Instrument and Control Engineers, Vol.34, No.8, pp.977-985,1998.
  • J.Hu, K.Kumamaru and K.Inoue, " A Hybrid Robust Identification Using Genetic Algorithm and Gradient Method ", Trans. of the Society of Instrument and Control Engineers, Vol.32, No.5, pp.714-721,1996.

 

Proceeding Papers before 2008

  • Y. Chen, J. Hu, K. Hirasawa and S. Yu, "Performance Tuning of Genetic Algorithm with Reserve Selection", in Proc. of 2007 IEEE Congress on Evolutionary Computation (CEC2007) (Sigapore), 9, 2007, pp.2202-2209.
  • Y. Chen, J. Hu, K. Hirasawa and S. Yu, "Optimizing Reserve Size in Genetic Algorithms with Reserve Selection Using Reinforcement Learning", in Proc. of SICE Annual Conference 2007 (Kagawa), 9, 2007, pp.1341-1347.
  • Y. Xu, J. Hu, K. Hirasawa and X. Pang, "A New Cooperative Approach to Discrete Particle Swarm", in Proc. of SICE Annual Conference 2007 (Kagawa), 9, 2007, pp.1311-1318.
  • Y. Chen, J. Hu, K. Hirasawa and S. Yu, "GARS: An Improved Genetic Algorithm with Reserve Selection for Global Optimization", in Proc. of 2007 Genetic and Evolutionary Computation Conference (GECCO2007),  University College London, London, England, 7, 2007, pp. 1173-1178.
  • J.Hu, T.Sasakawa, K.Hirasawa and H.Zheng, "A Hierarchical Learning System Incorporating with Supervised, Unsupervised and Reinforcement Learning", LNCS 4491: Advances in Neural Network - ISNN 2007 (Proc of 4th International Symposium on Neural Networks (Nanjing)), Part I, 5, 2007, pp.403-412.
  • L. Huang, J. Hu and K. Hirasawa, "A Quasi-ARMA Model for Financial Time Series Prediction", in Proc. the 38th ISCIE International Symposium on Stochastic Systems Theory and Its Applications (SSS2006) (Nagano), 11, 2006, pp.64-69.
  • B.Li, J.Hu and K.Hirasawa, "Fuzzy Decision-making SVM with An Offset for Real-world Lopsided Data Classification", in Proc. of SICE-ICASE International Joint Conference 2006 (Busan), 10, 2006, pp.143-148.
  • T.Sasakawa, J.Hu, K.Isono and K.Hirasawa, "Effective Training Methods for Function Localization Neural Networks", in Proc. of  International Joint Conference on Neural Networks (Vancouver), 7, 2006, pp.9535-9540
  • B.Li, J.Hu, K.Hirasawa, P.Sun and K.Marko, "Support Vector Machine with Fuzzy Decision-Making for Real-world Data Classifiction", in Proc. of  International Joint Conference on Neural Networks (Vancouver), 7, 2006, pp.1314-1319
  • T.Sasakawa, J.Hu and K.Hirasawa, "Performance Optimization of Function Localization Neural Network by Using Reinforcement Learning", in Proc. of International Joint Conference on Neural Networks (Montreal), 8, 2005, pp.1314-1319
  • J.Hu, Y.Li and K.Hirasawa, "A Neural Network Approach to Improving Identification of Nonlinear Polynomial Models", in Proc. of SICE Annual Confference (Okayama), 8, 2005, pp.1662-1667
  • J.Hu, X.Lu and K.Hirasawa, "Training Quasi-ARX Neural Network Model by Homotopy Approach", in Proc. of SICE Annual Conference (Hokkaido), 8, 2004, pp.367-372.
  • T.Sasakawa, J.Hu and K.Hirasawa, "Self-organized Function Localization Neural Network", in Proc. of  International Joint Conference on Neural Networks (Budapest), 7, 2004
  • J.Hu, K.Hirasawa and H.Miyazaki, "An Adaptive Random Search Algorithm with Tuning Capabilities", in Proc of the 34th ISCIE International Symposium on Stochastic System Theory and Its Applications (Fukuoka), 10, 2002, pp.148-153.
  • J.Hu and K.Hirasawa, "A Method for Applying  Multilayer Perceptrons to Control of Nonlinear Systems", in Proc. of 9th International Conference on Neural Information Processing (ICONIP'02) (Singapore), 11, 2002, pp.1267-1271.
  • J.Hu, K.Hirasawa and K.Kumamaru, " A Quasi-ARX Model Incorporating Neural Networks for Control of Nonlinear Systems ", in Proc. of the 15th IFAC World Congress (Barcelona), 7, 2002.
  • J.Hu and K.Hirasawa, " A Hierarchical Method for Training Embedded Sigmoidal Neural Networks ", in Proc. of International Conference on Artificial Neural Networks (ICANN2001) (Wienna), 8, 2001, pp.937-942.
  • J.Hu and K.Hirasawa, " An Embedded Sigmoidal Neural Network for Modeling of Nonlinear Systems ", in Proc. of IEEE International Joint Conference on Neural Network (Washington), vol.3, 7, 2001, pp.1698-1703.
  • J.Hu and K.Hirasawa, "Overlapped Multi-Neural-Network: A Case Study ",  in Proc. of IEEE International Joint Conference on Neural Networks (Como), vol.I, 7, 2000,pp.120-125.
  • J.Hu, K.Kumamaru and K.Hirasawa, "Quasi-ARMAX Modeling Approaches to Identification and Prediction of Nonlinear Systems", in Proc. of the 12th IFAC Symp. on Identification (Santa Barbara), 6, 2000 (CDROM: FrMD3-2).
  • J.Hu and K.Hirasawa, "Adaptive Random Search Approach to Identification of Neural Network Model ", in Proc. of the 31th ISCIE International Symposium on Stochastic Systems Theory and Its Applications (Yokohama), 11,1999, pp.73-78.
  • J.Hu, K.Hirasawa and K.Kumamaru, "Adaptive Predictor for Control of Nonlinear Systems Based on Neurofuzzy Models ",  in Proc. of European Control Conference (Karlsruhe), 8, 1999  (CDROM: Thursday, Session CM-7).
  • J.Hu and K.Hirasawa, "Object Oriented Learning Network and Its Applications ",  in Proc. of IEEE International Joint Conference on Neural Networks (Washington), 7, 1999.
  • J.Hu, K.Kumamaru,.K.Hirasawa and K.Inoue, "An Indirect Approach to Adaptive Control of Nonlinear Systems Using Quasi-ARMAX Model ",  in Proc. of the 14th IFAC World Congress  (Beijing),  vol.I,   7, 1999, pp.391-396.
  • J.Hu, K.Hirasawa, C.Jin and T.Matsuoka, " Control of Nonlinear Systems Based on a Probabilistic Learning Network ",  in Proc. of the 14th IFAC World Congress  (Beijing), vol.C, 7, 1999, pp.447-452.
  • J. Hu, K.. Hirasawa, J. Murata and M. Ohbayashi, "A Computation Scheme for Higher Order Derivatives in Universal Learning Networks", in Proc. of 1998 IEEE International Conference on Intelligent Engineering Systems (INES'98) (Vienna), 9, 1998, pp.349-354.
  • J.Hu, K.Hirasawa and K.Kumamaru, " Identification of ARMAX Model Based on Homotopy Approaches ", in Proc. of the 30th ISCIE International Symposium on Stochastic Systems Theory and Its Applications (Kyoto), 11,1998, pp.87-92.
  • J.Hu, K.Hirasawa, J.Murata, M.Ohbayashi and Y.Eki, " A New Random Search Method for Neural Network Learning -RasID",  in Proc. of IEEE International Joint Conference on Neural Networks (Alaska), 5, 1998, pp.2346-2351.
  • J.Hu, K.Hirasawa, J.Murata, M.Ohbayashi and K.Kumamaru, " Adaptive Control of Nonlinear Black-Box Systems Based on Universal Learning Networks ",  in Proc. of IEEE International Joint Conference on Neural Networks (Alaska), 5, 1998, pp.2453-2458.
  • J.Hu, K.Hirasawa, J.Murata, M.Ohbayashi and K.Kumamaru, " Identification of Nonlinear Black-Box Systems Based on Universal Learning Networks ",  in Proc. of IEEE International Joint Conference on Neural Networks (Alaska), 5, 1998, pp.2465-2470.
  • J.Hu, K.Hirasawa and K.Kumamaru, "Fuzzy Models Embedding of STR Controller for Nonlinear Stochastic Systems",  in Proc. of the 29th ISCIE international Symposium on Stochastic Systems Theory and Its Applications (Tokyo), 11, 1997, pp.51-56.
  • J.Hu, K.Kumamaru,  K. Inoue and K.Hirasawa, " KDI-Based Robust Fault Detection Scheme for Nearly Linear Systems",  in Proc. of the 29th ISCIE international Symposium on Stochastic Systems Theory and Its Applications (Tokyo), 11, 1997, pp.13-18.
  • K.Kumamaru, J.Hu, K.Inoue and T.Soderstrom, " Fault Detection of Nonlinear Systems by Using Hybrid Quasi-ARMAX Models ", in Proc. of IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes (Kingston Upon Hull), 8, 1997, pp.1126-1131.
  • K.Kumamaru, J.Hu, K.Inoue and T.Soderstrom, "A Method of Robust Fault Detection for Dynamic Systems by Using Quasi-ARMAX Modeling ", in Proc. of the 11th IFAC Symp. on Identification (Kitakyushu), 7, 1997, Vol.3, pp.1207-1212.
  • J.Hu, K.Kumamaru and K. Inoue, " A Hybrid Quasi-ARMAX Modeling Scheme for Identification and Control of Nonlinear Systems ",  in Proc. of the 35th IEEE Conference on Decision and Control (Kobe), 12, 1996, pp.1413-1418.
  • J.Hu, K.Kumamaru and K. Inoue, "Adaptive Control of Nonlinear Stochastic Systems Based on a Hybrid Quasi-ARMAX Model ",  in Proc. of the 28th ISCIE international Symposium on Stochastic Systems Theory and Its Applications (Kyoto), 11, 1996, pp.149-154.
  • K.Kumamaru, J.Hu, K.Inoue and T.Soderstrom, " Robust Fault Detection Using Index of Kullback Discrimination Information ", in Proc. of the 13th IFAC World Congress  (San Francisco), 6, 1996, pp.205-210.
  • J.Hu, K.Kumamaru and K. Inoue, "A Guaranteed Nonlinear System Identification Using ARX Networks", in Proc. of the 27th ISCIE international Symposium on Stochastic Systems Theory and Its Applications (Beppu), 11, 1995, pp.7-12.
  • J.Hu and K.Kumamaru, "Identification of Nonlinear Systems Based on Adaptive Fuzzy Systems Embedding Quasi-ARMAX Model", in Proc. of the 34th SICE Annual Conference (international session) (Sapporo), 7, 1995, pp.1211-1216.
  • K.Kumamaru, J.Hu, K.Inoue and H.Ono, " Fault Detection via KDI in Presence of Unmodelled Uncertainty ", in Proc. of the 26th ISCIE international Symposium on Stochastic Systems Theory and Its Applications (Kyoto), 11, 1994, pp.173-178.