Advances in Swarm Intelligence

1. Front Matter

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2. Hybrid Algorithms

   1. Hybrid Gravitational Search and Clonal Selection Algorithm for Global Optimization

      • Shangce Gao, Hongjian Chai, Beibei Chen, Gang Yang

      Pages 1-10

   2. A Hybrid Genetic Programming with Particle Swarm Optimization

      • Feng Qi, Yinghong Ma, Xiyu Liu, Guangyong Ji

      Pages 11-18

   3. A Physarum Network Evolution Model Based on IBTM

      • Yuxin Liu, Zili Zhang, Chao Gao, Yuheng Wu, Tao Qian

      Pages 19-26

   4. Cultural Algorithms for the Set Covering Problem

      • Broderick Crawford, Ricardo Soto, Eric Monfroy

      Pages 27-34

   5. Impulse Engine Ignition Algorithm Based on Genetic Particle Swarm Optimization

      • Xiaolong Liang, Zhonghai Yin, Yali Wang, Qiang Sun

      Pages 35-43

3. Swarm-Robot and Multi-agent Systems

   1. Learning by Imitation for the Improvement of the Individual and the Social Behaviors of Self-organized Autonomous Agents

      • Abdelhak Chatty, Philippe Gaussier, Ilhem Kallel, Philippe Laroque, Adel M. Alimi

      Pages 44-52

   2. An Indexed K-D Tree for Neighborhood Generation in Swarm Robotics Simulation

      • Zhongyang Zheng, Ying Tan

      Pages 53-62

   3. Agent-Based Social Simulation and PSO

      • Andreas Janecek, Tobias Jordan, Fernando Buarque de Lima-Neto

      Pages 63-73

   4. Multi-agent Oriented Stable Payoff with Cooperative Game

      • Tianwen Li, Feng Ma, Weiyi Liu

      Pages 74-81

4. Support Vector Machines

   1. Use the Core Clusters for the Initialization of the Clustering Based on One-Class Support Vector Machine

      • Lei Gu

      Pages 82-88

   2. Terrain Image Classification with SVM

      • Mu-Song Chen, Chipan Hwang, Tze-Yee Ho

      Pages 89-97

   3. A Novel Algorithm for Kernel Optimization of Support Vector Machine

      • Lijie Li

      Pages 98-105

   4. Training Least-Square SVM by a Recurrent Neural Network Based on Fuzzy c-mean Approach

      • Fengqiu Liu, Jianmin Wang, Sitian Qin

      Pages 106-113

5. Data Mining Methods

   1. A Locality Sensitive K-Means Clustering Method Based on Genetic Algorithms

      • Lei Gu

      Pages 114-119

   2. Using Graph Clustering for Community Discovery in Web-Based Social Networks

      • Jackson Gomes Souza, Edeilson Milhomem Silva, Parcilene Fernandes Brito, José Alfredo F. Costa, Ana Carolina Salgado, Silvio R. L. Meira

      Pages 120-129

   3. Application of Dynamic Rival Penalized Competitive Learning on the Clustering Analysis of Seismic Data

      • Hui Wang, Yan Li, Lei Li

      Pages 130-136

   4. An Online Trend Analysis Method for Measuring Data Based on Historical Data Clustering

      • Jianfeng Qu, Maoyun Guo, Yi Chai, Zhimin Yang, Tao Zou, Tian Lan et al.

      Pages 137-145

   5. Measuring Micro-blogging User Influence Based on User-Tweet Interaction Model

      • Dong Liu, Quanyuan Wu, Weihong Han

      Pages 146-153

   6. Discover Community Leader in Social Network with PageRank

      • Rui Wang, Weilai Zhang, Han Deng, Nanli Wang, Qing Miao, Xinchao Zhao

      Pages 154-162

This book and its companion volume, LNCS vols. 7928 and 7929 constitute the proceedings of the 4th International Conference on Swarm Intelligence, ICSI 2013, held in Harbin, China in June 2013. The 129 revised full papers presented were carefully reviewed and selected from 268 submissions. The papers are organized in 22 cohesive sections covering all major topics of swarm intelligence research and developments. The topics covered in this volume are: hybrid algorithms, swarm-robot and multi-agent systems, support vector machines, data mining methods, system and information security, intelligent control, wireless sensor network, scheduling and path planning, image and video processing, and other applications.

• applications
• design
• graphs
• machine learning
• optimization algorithms
• algorithm analysis and problem complexity

• Key Laboratory of Machine Perception (MOE), School of lectronics Engineering and Computer Science, Department of Machine Intelligence, Peking University, Beijing, China

  Ying Tan

• Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

  Yuhui Shi

• Automation College, Harbin Engineering University, Harbin, China

  Hongwei Mo

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