Basic Information

Jiang-She Zhang
Professor of School of Mathematics and Statistics, 
Xi’an Jiaotong University

Contact

Address:  School of Mathematics and Statistics,
                Xi’an Jiaotong University,
                No.28 Xianning West Road

                Xi'an, Shaanxi, 710049, P.R. China.

Tel: 86-029-82665961

Fax:86-029-82668551

E-Mail: jszhang@mail.xjtu.edu.cn

闹钟

Visitors

Research Interests

Interests and Research Areas

  • Robust Clustering
  • Face Recognition
  • Sparse encoding
  • Deep Learning
  • Hyperspectral analysis (unmixing, fusion)
  • Short-term load forecasting for electric power system
  • Bayesian learning
  • Global optimization
  • Ensemble learning

Publications

Publications in 2019

  1. Kai Sun, Jiangshe Zhang, Hongwei Yong, Junmin Liu, FPCANet: Fisher discrimination for Principal Component Analysis NetworkKNOWLEDGE-BASED SYSTEMS166: 108-117, 2019.
  2. Zengjie Song, Jiangshe Zhang, Guang Shi,  Junmin Liu, Fast Inference Predictive Coding: A Novel Model for Constructing Deep Neural Networks, Accepted by  IEEE Transactions on Neural Networks and Learning Systems,  DOI: 10.1109/TNNLS.2018.2862866.
  3. Qiao Ke, Jiangshe Zhang, Wei Wei, Robertas Damasevicius, Marcin Wozniak, Adaptive Independent Subspace Analysis of Brain Magnetic Resonance Imaging Data. IEEE Access 7: 12252-12261 (2019).

 

Publications in 2018

  1. Peiju Chang, Jiangshe Zhang, Junying Hu, Zengjie Song, A deep neural network based on ELM for semi-supervised learning of image classification, NEURAL PROCESSING LETTERS, in press, doi: 10.1007/s11063-017-9709-0, 2018.
  2. Chunxia Zhang, Jiangshe Zhang, Guanwei Wang, Nannan Ji, A novel bagging approach for variable ranking and selection via a mixed importance measure, JOURNAL OF APPLIED STATISTICS, in press, doi: 10.1080/02664763.2017.1391181, 2018.
  3. Chunxia Zhang, Jiangshe Zhang, Qingyan Yin, Early stopping aggregation in selective variable selection ensembles for high-dimensional linear regression models, KNOWLEDGE-BASED SYSTEMS, in press, doi: 10.1016/j.knosys.2018.04.016, 2018. 
  4. Changsheng Zhou,  Jiangshe Zhang, et al. Lp-WGAN: Accelerate and Stabilize WGAN via Normalizing Weights,  KNOWLEDGE-BASED SYSTEMS, 161: 415-424, 2018. 
  5. Guang Shi, Jiangshe Zhang, Nannan Ji, Changpeng Wang, A New Variant of Restricted Boltzmann Machine with Horizontal Connections, Neural Computing and Applications, https://doi.org/10.1007/s00521-018-3460-y, 2018.
  6. Guang Shi, Jiangshe Zhang, Huirong Li, Changpeng Wang, Enhance the performance of deep neural networks via L2 regularization on the input of activations, Neural Processing Letters,  https://doi.org/10.1007/s11063-018-9883-8, 2018.
  7. Fang Du, Jiangshe Zhang, Nannan Ji, Guang Shi, Chunxia Zhang, An effective hierarchical extreme learning machine based multimodal fusion framework. Neurocomputing 322: 141-150 (2018). 
  8. Changpeng Wang, Xueli Song, Jiangshe Zhang, Graph Regularized Nonnegative Matrix Factorization with Sample Diversity for Image Representation,  Eng. Appl. of AI, 68: 32-39 (2018).
  9. Changpeng Wang, Jiangshe Zhang, Fang Du, Guang Shi, Symmetric low-rank representation with adaptive distance penalty for semi-supervised learning. Neurocomputing, 316: 376-385 (2018).

 

Publications in 2017

  1. Kai Sun, Jiangshe Zhang, Chunxia Zhang, Junying Hu, Generalized extreme learning machine autoencoder and a new deep neural network, Neurocomputing, 230(2017) :374–381. (Highly Cited & Hot Paper)
  2. Chunxia Zhang, Jiangshe Zhang, Qingyan Yin, A ranking-based strategy to prune variable selection ensembles, KNOWLEDGE-BASED SYSTEMS, 125: 13-25, 2017. 
  3. Junying Hu, Jiangshe Zhang, Nannan Ji, Chunxia Zhang,  A new regularized restricted Boltzmann machine based on class preserving. KNOWLEDGE-BASED SYSTEMS, 2017, 123: 1-17. 
  4. Jiangshe Zhang, Weifu Ding, Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine: The Case of Hong Kong, INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 14(2): 114, 2017.
  5. Huirong Li, Jiangshe Zhang, Junying Hu, Chunxia Zhang, Junmin Liu, Graph-based discriminative concept factorization for data representation, KNOWLEDGE-BASED SYSTEMS, 118:70-79, 2017.

Publications in 2016

  1. Chunxia Zhang, Jiangshe Zhang, Sang-Woon Kim, PBoostGA: pseudo-boosting genetic algorithm for variable ranking and selection, COMPUTATIONAL STATISTICS, 31(4): 1237-1262, 2016. 
  2. Junmin Liu, Chunxia Zhang, Jiangshe Zhang, Huirong Li, Yuelin Gao,  Manifold regularization for sparse unmixing of hyperspectral images. SPRINGERPLUS, 2016, (5): 2007. 
  3. Wei-fu Ding, Jiangshe Zhang, Yee Leung, Prediction of air pollutant concentration based on sparse response back-propagation training feedforward neural networks[J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2016, 23(19): 19481-19494. 
  4. Sheng-cai Liu, Jiang-she Zhang, Jun-min Liu, et al. (ell _{1/2,1), group sparse regularization for compressive sensing[J]. Signal, Image and Video Processing, 2016, 10(5):861-868.
  5. Zeng-jie Song, Jiangshe Zhang, Jun-min Liu, No-Reference Image Quality Assessment Using Image Saliency for JPEG Compressed Images, Journal of Imaging Science and Technology, Advance online publication, DoI: http://dx.doi.org/10.2352/J.ImagingSci.Technol.2016.60.6.060403, May 2016.
  6. Hui-rong Li, Jiangshe Zhang, Chang-peng Wang, Jun-min Liu.Manifold regularized non-negative matrix factorization with label information. Journal of Electronic Imaging, 25(2), 023023,2016.
  7. Hui-rong Li, Jiangshe Zhang, Jun-min Liu.Class-driven concept factorization for image representation. Neurocomputing, 190 (2016) :197–208.
  8. Wei-fu Ding, Jiangshe Zhang, Yee Leung. Prediction of air pollutant concentrat in based on sparse response back-propagation training feedforward neural networks, Environ Sci Pollut Res (2016) 23:19481–19494
  9. Liu, J., Zhang, C., Zhang J., Li, H., and Gao, Y. "Manifold regularization for sparse unmixing of hyperspectral images", Accepted by SpringerPlus, 2016.
  10. Chun-xia Zhang, Jiang-she Zhang, Sang-Woon Kim "PBoostGA: pseudo-boosting genetic algorithm for variable ranking and selection." Comput. Stat., 2016, 31(4): 1237-1262. 
  11. Wang, Juan, Zhang Jiangshe, Zhao, Jie, "Texture Classification Using Scattering Statistical and Cooccurrence Features", MATHEMATICAL PROBLEMS IN ENGINEERING, 2016, DOI: 10.1155/2016/3946312.
  12. Wang, Juan, Zhang Jiangshe, Zhao Mingming, "On size invariance texture image retrieval by fuzzy logic classifier and scattering statistical features", PATTERN ANALYSIS AND APPLICATIONS, 2016, 19(2): 509-516. 

 

Publications in 2015

  1. Jiang-she Zhang, Chang-peng Wang, Yu-qian Yang. Learning latent features by nonnegative matrix factorization combining similarity judgments. Neurocomputing, 2015, 55: 43-52.
  2. Jiang-she Zhang, Nan-nan Ji, Jun-min Liu, Ji-Yuan Pan, De-yu Meng. Enhancing performance of the backpropagation algorithm via sparse response regularization. Neurocomputing, 2015, 153: 20-40.
  3. Chang-peng Wang, Jiang-she Zhang, Guo-dong Chang, Qiao Ke. Singular Value Decomposition Projection for solving the small sample size problem in face recognition. Journal of visual communication and image representation, 2015, 26: 265-274.
  4. Jun-ying Hu, Jiang-she Zhang, Chun-xia Zhang, Juan Wang. A new deep neural network based on a stack of single-hidden-layer feedforward neural networks with randomly fixed hidden neurons[J]. Neurocomputing, 2015, 171(C):63-72.

Publications in 2014 and 2013

  1. Chun-xia Zhang, Guan-wei Wang, Jiang-she Zhang, Gao Guo, Qing-yan Yin. IRUSRT: A Novel Imbalanced Learning Technique by Combining Inverse Random Under Sampling and Random Tree. COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2014, 43(10): 2714-2731.
  2. Nan-nan Ji, Jiang-she Zhang, Chun-xia Zhang. A sparse-response deep belief network based on rate distortion theory. Pattern Recognition, 2014, 47(9): 3179-3191.
  3. Nan-nan Ji, Jiang-she Zhang, Chun-xia Zhang, Lei Wang. Discriminative restricted Boltzmann machine for invariant pattern recognition with linear transformations.Pattern Recognition Letters, 2014, 45: 172-180.
  4. Nan-nan Ji, Jiang-she Zhang, Chun-xia Zhang, Qingyang Yin. Enhancing performance of restricted Boltzmann machines via log-sum regularization. KNOWLEDGE-BASED SYSTEMS, 2014, 63: 82-96. 
  5. Chun-xia Zhang, Jiang-she Zhang, Nan-nan Ji, Gao Guo. Learning ensemble classifiers via restricted Boltzmann machines. Pattern Recognition Letters, 2014, 36: 161-170. 
  6. Jun-min Liu, Yi-jun Chen, Jiang-she Zhang, and Zongben Xu. Enhancing low-rank subspace clustering by manifold regularization. IEEE Transactions on Image Processing, 2014, 23(9): 4022-4030.
  7. Jun-min Liu, Jiang-she Zhang. Spectral unmixing via compressive sensing. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(11): 7099-7110. PDF ,Code.
  8. Yee Leung, Jun-min Liu, Jiang-she Zhang. An improved adaptive Intensity-Hue-Saturation method for the fusion of remote sensing images. IEEE Geoscience and Remote Sensing Letters, 2014, 11(5): 985-989. (SCI, 2012 Impact Factor: 1.823) . PDF
  9. Xu Qin, Jiang-she Zhang, Xiao-dong Yan. Model selection of the generalized von Mises distribution based on empirical mode decomposition with data analyses. Statistical Methodology, 2013, 14: 15-25.
  10. Qing-yan Yin, Jiang-she Zhang, Chun-xia Zhang, et al. An empirical study on the performance of cost-sensitive boosting algorithms with different levels of class imbalance. Mathematical Problem in Engineering, 2013, DOI: 10.1155/2013/761814.  

Publications in 2012

1.       Fei Zang, Jiang-She Zhang, Ji-Yuan Pan. Face recognition using elasticfaces. Pattern Recognition, 2012, 45(11): 3866-3876. (SCI, 2012 Impact Factor: 2.632).  PDF 
2.       Fei Zang, Jiang-She Zhang. Label propagation through sparse neighborhood and its applications. Neurocomputing, 2012, 97: 267-277. (SCI, 2012 Impact Factor: 1.634). PDF
3.       Fei Zang, Jiang-She Zhang, Chun-Xia Zhang. Learning with power L1-graph for single labeled image biometric recognition. International Journal of the Physical Sciences, 2012, 7(10): 1633-1640. PDF
4.       Xu Qin, Jiang-she Zhang, Xiao-Dong Yan. Two improved mixture weibull models for the analysis of wind speed data. Journal of Applied Meteorology and Climatology, 2012, 51(7): 1321-1332. (SCI, 2012 Impact Factor: 2.020).
5.       Xu Qin, Jiang-She Zhang, Xiao-Dong Yan. A finite mixture three-parameter weibull model for the analysis of wind speed data. Communications in Statistics-Theory and Methods, 2012, 41(12): 2160-2171. (SCI, 2012 Impact Factor: 0.298). PDF
6.       Jun-Min Liu, Jiang-She Zhang. A new maximum simplex volume method based on householder transformation for endmember. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(1): 104-118. (SCI, 2012 Impact Factor: 3.467). PDF, Code.
7.       Jun-Min Liu, Jiang-She Zhang. Analysis and acceleration strategy of endmember extraction algorithms based on convex geometry.International Journal of Remote Sensing, 2012, 33(21): 6722-6748. (SCI, 2012 Impact Factor: 1.138). PDF, Code. 
8.       Chun-Hong Wang, Jiang-She Zhang, Xiao-Dong Yan. The use of geographically weighted regression for the relationship among extreme climate indices in China. Mathematical Problems in Engineering, vol. 2012, Article ID 369539, 15 pages, 2012. (SCI, 2012 Impact Factor: 1.383). PDF
9.       Chun-Xia Zhang, Guan-Wei Wang, Jiang-She Zhang. An empirical bias-variance analysis of DECORATE ensemble method at different training sample sizes. Journal fo Applied Statistics, 2012, 39(4): 829-850. (SCI, 2012 Impact Factor: 0.449). PDF
10.    Jun-Min Liu, Jiang-She Zhang, Yue-Lin Gao, Chun-Xia Zhang, Zhi-Hua Li. Enhancing spectral unmixing by local neighborhood weights. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2012, 5(5): 1545-1552. (SCI, 2012 Impact Factor: 2.874). PDF, Code. 
Publications in 2011
1.       Yu-Qian Yang, Jiang-She Zhang, Xing-Fang Huang. Adaptive image enhancement algorithm combining kernel regression and local homogeneity. Mathematical Problems in Engineering, 2011, Article ID: 693532, 14 pages. (SCI, 2011 Impact Factor: 0.689). PDF
2.       Fei Zang, Jiang-She Zhang. Discriminative learning by sparse representation for classification. Neurocomputing, 2011, 74(12-13): 2176-2183. (SCI, 2011 Impact Factor:1.429). PDF
3.       Ji-Yuan Pan, Jiang-She Zhang. Relationship matrix nonnegative decomposition for clustering. Mathematical Problems in Engineering, 2011, Article ID: 864540, 15pages (SCI, 2011 Impact Factor: 0.689). PDF
4.       Lei Wang, Jiang-She Zhang, Fei Zang. An efficient feature extraction method, global between maximum and local within minimum, and its applications. Mathematical Problems in Engineering, 2011, Article ID: 176058, 16 pages. (SCI, 2011 Impact Factor:0.689). PDF
5.       Ji-Yuan Pan, Jiang-She Zhang. Large margin based nonnegative matrix factorization and partial least squares regression for face recognition, Pattern Recognition Letters, 2011, 32(14): 1822-1835. (SCI, 2011 Impact Factor: 1.213). PDF
6.       Xu Qin, Jiang-She Zhang, Xiao-Dong Yan. Local linear least squares kernel regression for linear and circular predictors. Communications in Statistics-Theory and Methods, 2011, 40(21): 3812-3823. (SCI, 2011 Impact Factor: 0.351). PDF
7.       Xu Qin, Jiang-She Zhang, Xiao-Dong Yan. A nonparametric circular-linear multivariate regression model with a rule-of-thumb bandwidth selector. Computers & Mathematics with Applications, 2011, 62(8): 3048-3055 (SCI, 2011 Impact Factor: 1.472). PDF
8.       Zang F, Zhang JS. Softmax discriminant classifier. The Third International Conference on Multimedia Information Networking and Security, Shanghai, China, 2011, 16-19. PDF
9.    Xu Qin, Jiang-She Zhang, Xiao-Dong Yan. A nonparametric circular-linear multivariate regression model with a its application to wind energy. International Mathematical Forum, 2011, 6(53): 2615-2624. PDF
 
some publications before 2011
1.    Chun-Xia Zhang, Jiang-She Zhang. A variant of rotation forest for constructing ensemble classifiers. Pattern Analysis and Applications, 2010, 19(4): 59-77. (SCI, 2011 Impact Factor: 1.081). PDF
2.    Gao Guo, Jiang-She Zhang, Gai-Ying Zhang. A method to sparsify the solution of support vector regression. Neural Computing & Applications, 2010, 19(1): 115-122. (SCI, 2011 Impact Factor: 0.563). PDF
3.    Gai-Ying Zhang, Gao Guo, Jiang-She Zhang. SVR plus RVR: a robust sparse kernel method for regression. International Journal on Aritifcial Intelligence Tools, 2010, 19(5): 627-645. (SCI, 2011 Impact Factor: 0.320). PDF
4.    Xing-Fang Huang, Pei-Hua Qiu. Blind deconvolution for jump-preserving curve estimation. Mathematical Problems in Engineering, 2010, Article ID: 350849, 9 pages. (SCI, 2011 Impact Factor: 0.689). PDF
5.    Gai-Ying Zhang, Chun-Xia Zhang, Jiang-She Zhang. Out-of-bag estimation of the optimal hyperparameter in subbag ensemble method. Communications in Statistics-Simulation and Computation, 2010, 39(10): 1877-1892. (SCI, 2011 Impact Factor: 0.343). PDF
6.    Qin Xu, Jiang-She Zhang, Xiao-Dong Yan. A new circular distribution and its application to wind data. Journal of Mathematics Research, 2010, 2(3): 12-17.
7.    Chun-Hong Wang, Jiang-She Zhang, Xiao-Dong Yan. Investigating the relationship among extreme climate indices by a varying-coefficient regression model. Proceedings of the International Conference on Computer Application and System Modeling (ICCASM), 2010, 2: V2-344-349.
8.    Chun-Xia Zhang, Jiang-She Zhang, Gai-Ying Zhang. Using boosting to prune double-bagging ensembles. Computational Statistics & Data Analysis, 2009, 53(4): 1218-1231 (SCI, 2011 Impact Factor: 1.089). PDF
9.    Chun-Xia Zhang, Jiang-She Zhang. A novel method for constructing ensemble classifiers. Statistics and Computing, 2009, 19(3): 317-327 (SCI, 2011 Impact Factor: 1.089). PDF
10.    Gao Guo, Jiang-She Zhang, Gai-Ying Zhang. A method to sparsify the solution of support vector regression. Neural Computing and Applications, 2009, 18(8): 919-926 (SCI, 2011 Impact Factor: 0.563).
11.    Xing-Fang Huang, Jiang-She Zhang. Edge-preserving filtering for grey and color image. Proceedings of the WRI World Congress on Computer Science and Information Engineering, Los Angeles, California USA, 2009, 5: 139-143.
12.    Qin Xu, Zhang JS, Yan XD. A finite mixture three-parameter weibull model for the analysis of wind speed data. International Conference on Computational Intelligence and Software Engineering, 2009, 1-3.
13.    王春红, 张讲社, 延晓东, 秦旭. 1961~2005年漠河年均温和年均高低温的变化分析. 数学的实践与认识, 2009, 39(11): 62-68.
14.    秦旭, 张讲社, 延晓冬. 基于改进的EMD的运城市持续极端气温的初步分析. 大气科学学报, 2009, 32(5): 645-651.
15.    Yong-Jun Wang, Jiang-She Zhang. A new constructing auxiliary function method for global optimization. Mathematical and Computer Modelling, 2008, 47(11-12):1396-1410. (SCI, 2011 Impact Factor: 1.066)
16.    Chun-Xia Zhang, Jiang-She Zhang. A local boosting algorithm for solving classification problems. Computational Statistics & Data Analysis, 2008, 52(4): 1928-1941. (SCI, 2011 Impact Factor: 1.089).
17.    Chun-Xia Zhang, Jiang-She Zhang, Gai-Ying Zhang. An efficient modified boosting method for solving classification problems. Journal of Computational and Applied Mathematics, 2008, 214(2): 381-392. (SCI, 2011 Impact Factor: 1.029). PDF
18.    Chun-Xia Zhang, Jiang-She Zhang, Guan-Wei Wang. An empirical study of using Rotation Forest to improve regressors. Applied Mathematics and Computation, 2008, 195(2): 618-629. (SCI, 2011 Impact Factor: 1.534).
19.    Chun-Xia Zhang, Jiang-She Zhang. RotBoost: A technique for combining Rotation Forest and AdaBoost. Pattern Recognition Letters, 2008, 29(10): 1524-1536. (SCI, 2011 Impact Factor: 1.213). PDF
20.    Yong-Jun Wang, Jiang-She Zhang. A Hybrid Fast Descent Method for Globally Optimizing High Dimensional Functions. Dynamics of Continuous, Discrete & Impulsive Systems B: Algorithms and Applications, 2008, 15(1): 87-98.
21.    Jiang-She Zhang, Yu-Qian Yang, Xiao-Wen Chen, Cheng-Hu Zhou. The Enhanced Piecewise Regression Based on Deterministic Annealing. Science in China Series F: Information Sciences, 2008, 51(8): 1025-1038. (SCI, 2011 Impact Factor: 0.642)
22.    张讲社, 杨雨茜, 陈晓文, 周成虎. 基于确定性退火的增强型分片回归. 中国科学F: 信息科学, 2008, 38(8): 1244-1254. 
23.    Yong-Jun Wang, Jiang-She Zhang and Gai-Ying Zhang. A dynamic clustering based differential evolution algorithm for global optimization. European Journal of Operational Research, 2007, 183(1): 56-73. (SCI, 2011 Impact Factor: 2.158). PDF
24.    Chun-Xia Zhang, Chang-Lin Mei, Jiang-She Zhang. An empirical study of a test for polynomial relationships in randomly right censored regression models, Computational Statistics & Data Analysis, 2007, 51(12): 6543-6556. (SCI, 2011 Impact Factor: 1.089)
25.    Gao Guo, Jiang-She Zhang. Reducing examples to accelerate support vector regression. Pattern Recognition Letters, 2007, 28(16): 2173-2183. (SCI, 2011 Impact Factor: 1.213). PDF
26.    Yong-Jun Wang, Jiang-She Zhang. An efficient algorithm for large scale global optimization of continuous functions. Journal of Computational and Applied Mathematics, 2007, 206(2): 1015-1026. (SCI, 2011 Impact Factor: 1.029). PDF
27.    Yong-Jun Wang, Jiang-She Zhang. Global optimization by an improved differential evolutionary algorithm. Applied Mathematics and Computation, 2007, 188(1): 669-680. (SCI, 2011 Impact Factor: 1.534)
28.    Jiang-She Zhang, Xing-Fang Huang, Cheng-Hu Zhou. An improved kernel regression method based on Taylor expansion. Applied Mathematics and Computation, 2007, 193(2): 419-429. (SCI, 2011 Impact Factor: 1.534)
29.    Chun-xia Zhang, Chang-lin Mei, Jiang-she Zhang. Influence Diagnostics in Partially Varying-Coefficient Models. Acta Mathematicae Applicatae Sinica, English Series, 2007, 23(4): 619-628. (SCI, 2011 Impact Factor: 0.371)
30.    Yong-Jun Wang, Jiang-She Zhang, Yu-Fen Zhang, An Effective and Efficient Two Stage Algorithm For Global Optimization, Advances in Machine Learning and Cybernetics - 4th International Conference, LNAI3930 (Lecture Notes in Artificial Intelligence Vol. 3930), 2006, 487-490, D.S. Yeung et al. (eds) (SCI, 2011 Impact Factor: 0.371)
 31.    Yong-Jun Wang, Jiang-She Zhang, Yu-Fen Zhang, A Fast Hybrid Algorithm For Global Optimization, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, August, 2005, 3030-3035.
 32.    Yong-Chang Jiao, Yee Leung, Zongben Xu, and Jiang-She Zhang, Variable Programming: A generalized Minimax Problem. Part I: Models and Theory, Computational Optimization and Applications, 2005, 30(3): 229-261. (SCI, 2011 Impact Factor: 1.274)
 33.    Yong-Chang Jiao, Yee Leung, Zongben Xu, and Jiang-She Zhang, Variable Programming: A generalized Minimax Problem. Part II: Algorithms, Computational Optimization and Applications, 2005, 30(3): 263-296. (SCI, 2011 Impact Factor: 1.274)
 34.    赵登福; 庞文晨; 张讲社; 王锡凡,基于支撑向量机的电力系统峰负荷预测; 西安交通大学学报, 2005, 39(4): 398-401. 
 35.    赵登福; 庞文晨; 张讲社; 王锡凡,基于贝叶斯理论和在线学习支持向量机的短期负荷预测,中国电机工程学报, 2005, 25(13): 8-13. 
 36.    张讲社,郭高,加权稳健支撑向量回归方法,计算机学报, 2005, 28(7): 1171-1177. 
 37.    Jiang-She Zhang, Yiu-Wing Leung. Improved Possibilistic C-Means Clustering Algorithms, IEEE Transactions on Fuzzy Systems, 2004, 12(2). (SCI, 2011 Impact Factor: 2.683). PDF
 38.    卢春阁,张讲社,一类基于模糊聚类和模糊推理的稳健分类器,模式识别与人工智能, 2004, 17(1): 60-65. 
 39.    Jiang-She Zhang, Yiu-Wing Leung. Robust Clustering by Pruning outlier, IEEE Trans. Systems, Man, and Cybernetics-part B: Cybernetics, 2003, 33(6): 983-999. (SCI, 2011 Impact Factor: 2.674). PDF
 40.    Pei Tao, Yang Ming, Zhang Jiang-she, Zhou Cheng-hu, Luo Jian-cheng, Li Quan-linMulti-scale expression of spatial activity anomalies of earthquakes and its indicative significance on the space and time attributes of strong earthquakes, ACTA Seismologica Sinica, 2003, 16(3):  292-303. 
 41.    赵登福,吴娟,刘昱,张讲社,王锡凡,基于事例推理的短期负荷预测,西安交通大学学报, 2003, 37(6): 608-611.
 42    裴涛,杨明,张讲社,地震空间活动性异常的多尺度表示及其对强震时空要素的指示作用, 地震学报, 2003, 25(3). 
 43.    赵登福,周琳,申旭辉,张讲社,王锡凡,基于正交最小二乘法模糊模型的短期负荷预测,西安交通大学学报2002, 36(4): 331-334. 
 44.    骆剑承,周成虎,梁怡,张讲社,黄叶芳,多尺度空间单元区域划分方法,地理学报, 2002, 57(2). 
 45.    赵登福,王蒙,张讲社,王锡凡,基于支撑向量机方法的短期负荷预测中国电机学报, 2002, 22(4).
 46.   Hong, Qiao, Jiang-She Zhang, and Zong-Ben, Xu, A new data processing method based on a biological model of the compound eye: Direction quantization representation, IEEE Trans. Systems, Man, and Cybernetics-part A, 2001, 31(3). (SCI, 2011 Impact Factor: 2.080). PDF
 47.    张讲社,梁怡,徐宗本, 基于视觉系统的聚类算法, 计算机学报, 2001, 24(5): 496-501. 
 48.    赵登福、王蒙,张讲社等,基于确定性退火方法的短期负荷预测,中国电机学报, 2001, 21(7). 
 49.    Yee Leung, Jiang-She Zhang, Zong-Ben Xu, Clustering by scale-space filtering, IEEE Trans. Pattern Analysis and Machine Intelligence, 2000, 22(12):1396-1410. (SCI, 2011 Impact Factor: 5.027). PDF
 50.    张讲社, 徐宗本, 阮奕文, 一类模拟生物复眼几何结构的数据处理方法——方向量子化表示的理论, 计算机学报, 2000, 23(6): 9-14.
 51.    张讲社, 徐宗本, 阮奕文, 一类模拟生物复眼几何结构的数据处理方法——方向量子化表示的应用, 计算机学报, 2000, 23(6): 15-19.
 52.    张讲社, 徐宗本, 基于视觉系统的聚类: 原理与算法, 工程数学, 2000, 17(5). 
 53.    Yiu-Wing Leung, Jiang-She Zhang, Zong-Ben Xu, Optimal Neural Network Algorithm For On-line String Matching, IEEE Trans. Systems, Man, and Cybernetics-part B: Cybernetics, 1998, 28(5). (SCI, 2011 Impact Factor: 2.674). PDF
 54.    Zong-Ben, Xu, Jiang-She Zhang, Yiu-Wing Leung, An approximate algorithm for computing multi dimensional convex hulls, Applied Mathematics and Computation, 1998, 94: 193-226. (SCI, 2011 Impact Factor: 1.534)
 55.    Yee Leung, Jiang-She Zhang, and Zong-Ben Xu. Neural networks for convex hull computation, IEEE Trans. Neural Networks, 1997, 8(3): 601-611. (SCI, 2011 Impact Factor: 2.624). PDF
 56.    Jiang-She Zhang, Zong-Ben Xu, Yee Leung, Global annealing genetic algorithm and its convergence analysis, Science in China (Series E), 1997, 40(4): 414-424. (SCI, 2011 Impact Factor: 0.729)
 57.    Zong-Ben, Xu, Jiang-She Zhang, Yiu-Wing Leung, A general CDC formulation for specializing the cell exclusion algorithms of finding all zeros of vector functions, Applied Mathematics and Computation, 1997, 86: 235-259. (SCI, 2011 Impact Factor: 1.534)
  58.    张讲社,徐宗本,梁怡,整体退火遗传算法及其收敛充要条件,中国科学, 1997, 27(2): 154-164. 
  59.    Zong-Ben Xu, Jiang-She Zhang, A cell exclusion algorithm for determining all the solutions of a nonlinear system of equations, Applied Mathematics and Computation, 1996, 80(2-3): 181-208. (SCI, 2011 Impact Factor: 1.534)
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