Intelligent Computing Theories and Application

1. Front Matter

   Pages I-XXI

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2. Evolutionary Computation and Learning

   1. Front Matter

      Pages 1-1

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   2. Gbest-Guided Covariance Matrix Adaptation Evolution Strategy for Large Scale Global Optimization

      • Zhang Fuxing, Zhang Tao, Wang Rui

      Pages 3-13

   3. A Fast Approximate Hypervolume Calculation Method by a Novel Decomposition Strategy

      • Weisen Tang, Hailin Liu, Lei Chen

      Pages 14-25

   4. Towards the Differentiation of Initial and Final Retention in Massive Open Online Courses

      • Raghad Al-Shabandar, Abir Hussain, Andy Laws, Robert Keight, Janet Lunn

      Pages 26-36

   5. An Evolutionary Algorithm for Autonomous Agents with Spiking Neural Networks

      • Xianghong Lin, Fanqi Shen, Kun Liu

      Pages 37-47

   6. Sparse Reconstruction with Bat Algorithm and Orthogonal Matching Pursuit

      • Chunmei Zhang, Xingjuan Cai, Zhentao Shi

      Pages 48-56

   7. Data Transfer and Extension for Mining Big Meteorological Data

      • Tianwen Huang, Fei Jiao

      Pages 57-66

3. Neural Networks

   1. Front Matter

      Pages 67-67

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   2. A Review of Image Recognition with Deep Convolutional Neural Network

      • Qing Liu, Ningyu Zhang, Wenzhu Yang, Sile Wang, Zhenchao Cui, Xiangyang Chen et al.

      Pages 69-80

   3. Enhance a Deep Neural Network Model for Twitter Sentiment Analysis by Incorporating User Behavioral Information

      • Ahmed Sulaiman M. Alharbi, Elise DeDoncker

      Pages 81-88

   4. Topological Structure Analysis of Developmental Spiking Neural Networks

      • Xianghong Lin, Ying Li, Jichang Zhao

      Pages 89-100

   5. A Unified Deep Neural Network for Scene Text Detection

      • Yixin Li, Jinwen Ma

      Pages 101-112

   6. Exploring the New Application of Morphological Neural Networks

      • Bin Sun, Naiqin Feng

      Pages 113-120

   7. An Improved Evolutionary Random Neural Networks Based on Particle Swarm Optimization and Input-to-Output Sensitivity

      • Qing-Hua Ling, Yu-Qing Song, Fei Han, Hu Lu

      Pages 121-127

4. Nature Inspired Computing and Optimization

   1. Front Matter

      Pages 129-129

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   2. Evolutionary Metaphor of Genetic Encoding for Self-organizable Robots

      • Kiwon Yeom

      Pages 131-139

   3. Hybrid Coordinating Algorithm for Flying Robots

      • Kiwon Yeom

      Pages 140-151

5. Signal Processing

   1. Front Matter

      Pages 153-153

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   2. A Method to Detecting Ventricular Tachycardia and Ventricular Fibrillation Based on Symbol Entropy and Wavelet Analysis

      • Yingda Wei, Qingfang Meng, Haihong Liu, Mingmin Liu, Hanyong Zhang

      Pages 155-164

This three-volume set LNCS 10361, LNCS 10362, and LNAI 10363 constitutes the refereed proceedings of the 13th International Conference on Intelligent Computing, ICIC 2017, held in Liverpool, UK, in August 2017.  
The 212 full papers and 20 short papers of the three proceedings volumes were carefully reviewed and selected from 612 submissions. This first volume of the set comprises 71 papers. The papers are organized in topical sections such as Evolutionary Computation and Learning; Neural Networks; Nature Inspired Computing and Optimization; Signal Processing; Pattern Recognition; Biometrics Recognition; Image Processing; Information Security; Virtual Reality and Human-Computer Interaction; Business Intelligence and Multimedia Technology; Genetic Algorithms; Biomedical Informatics Theory and Methods; Particle Swarm Optimization and Niche Technology; Swarm Intelligence and Optimization; Independent Component Analysis; Compressed Sensing and Sparse Coding; Natural Computing; Intelligent Computing in Computer Vision; Computational Intelligence and Security for Image Applications in Social Network; Neural Networks: Theory and Application.

• biological networks
• computer vision
• ensemble methods
• kernel methods
• neural networks
• artificial intelligence
• bioinformatics
• computational biology
• computational genomics
• data mining and clustering
• deep learning
• dimensionality reduction and manifold learning
• feature selection
• molecular sequence analysis
• motif discovery
• reinforcement learning
• semi-supervised learning
• supervised learning
• support vector machines
• unsupervised learning

• Tongji University, Shanghai, China

  De-Shuang Huang

• Politecnico di Bari, Bari, Italy

  Vitoantonio Bevilacqua

• University of Wollongong, North Wollongong, Australia

  Prashan Premaratne

• Indian Institute of Technology, Kanpur, India

  Phalguni Gupta

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