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ORCIDNeurocomputing, Volume 211
Volume 211, October 2016
- Shifei Ding, Zhongzhi Shi, Dacheng Tao
, Bo An:
Recent advances in Support Vector Machines. 1-3 - Niusha Shafiabady, Lam Hong Lee, Rajprasad Rajkumar, V. P. Kallimani, Nik Ahmad Akram, Dino Isa:
Using unsupervised clustering approach to train the Support Vector Machine for text classification. 4-10 - A. Ben Hamza:
A graph-theoretic approach to 3D shape classification. 11-21 - Husheng Guo, Wenjian Wang:
Support vector machine based on hierarchical and dynamical granulation. 22-33 - Samia Djemai, Belkacem Brahmi, Mohand Ouamer Bibi:
A primal-dual method for SVM training. 34-40 - Yang Yu, Yancheng Li, Jianchun Li, Xiaoyu Gu:
Self-adaptive step fruit fly algorithm optimized support vector regression model for dynamic response prediction of magnetorheological elastomer base isolator. 41-52 - Shuyuan Yang, Jiren Zhang, Shun Cui, Min Wang, Licheng Jiao:
Curvelet Support Value Filters (CSVFs) for image super-resolution. 53-59 - Jingjing Hu, Xiaolei Chen, Changyou Zhang:
Proactive service selection based on acquaintance model and LS-SVM. 60-65 - Xuesong Wang, Fei Huang, Yuhu Cheng:
Computational performance optimization of support vector machine based on support vectors. 66-71 - Maria Malvoni, Maria Grazia De Giorgi, Paolo Maria Congedo:
Photovoltaic forecast based on hybrid PCA-LSSVM using dimensionality reducted data. 72-83 - Nafiseh Parastalooi, Ali Amiri, Parisa Aliheidari:
Modified twin support vector regression. 84-97 - Qinqin Tao, Shu Zhan, Xiao-Hong Li, Toru Kurihara:
Robust face detection using local CNN and SVM based on kernel combination. 98-105 - Deepak Kumar, Manoj Thakur:
Weighted multicategory nonparallel planes SVM classifiers. 106-116 - Jebarani Evangeline S, S. Suresh Kumar, J. Jayakumar:
Torque modeling of Switched Reluctance Motor using LSSVM-DE. 117-128 - Jian Xun Peng, Karen Rafferty, Stuart Ferguson:
Building support vector machines in the context of regularized least squares. 129-142 - Mohammad Ali Ahmadi:
Toward reliable model for prediction Drilling Fluid Density at wellbore conditions: A LSSVM model. 143-149 - Huajuan Huang, Xiuxi Wei, Yongquan Zhou:
A sparse method for least squares twin support vector regression. 150-158 - Jingjing Zhong, Peter W. Tse, Dong Wang:
Novel Bayesian inference on optimal parameters of support vector machines and its application to industrial survey data classification. 159-171 - Jiancong Fan, Zhonghan Niu, Yongquan Liang, Zhongying Zhao:
Probability model selection and parameter evolutionary estimation for clustering imbalanced data without sampling. 172-181 - Huiyuan Fu, Huadong Ma, Yinxin Liu, Dawei Lu:
A vehicle classification system based on hierarchical multi-SVMs in crowded traffic scenes. 182-190 - Qiuling Hou, Ling Zhen, Naiyang Deng, Ling Jing:
Novel Grouping Method-based support vector machine plus for structured data. 191-201 - Peng Chen, Lifen Yuan, Yigang He, Shuai Luo:
An improved SVM classifier based on double chains quantum genetic algorithm and its application in analogue circuit diagnosis. 202-211 - Guo Zhou, Dengming Zhu, Yi Wei, Zhaoqi Wang, Yongquan Zhou:
Real-time online learning of Gaussian mixture model for opacity mapping. 212-220
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