Life System Modeling and Intelligent Computing

1. Front Matter

   PDF

2. The First Section: Advanced Evolutionary Computing Theory and Algorithms

   1. A Novel Ant Colony Optimization Algorithm in Application of Pheromone Diffusion

      • Peng Zhu, Ming-sheng Zhao, Tian-chi He

      Pages 1-8

   2. Modelling the Effects of Operating Conditions on Motor Power Consumption in Single Screw Extrusion

      • Chamil Abeykoon, Marion McAfee, Kang Li, Peter J. Martin, Jing Deng, Adrian L. Kelly

      Pages 9-20

   3. Quantum Genetic Algorithm for Hybrid Flow Shop Scheduling Problems to Minimize Total Completion Time

      • Qun Niu, Fang zhou, Taijin Zhou

      Pages 21-29

   4. Re-diversified Particle Swarm Optimization

      • Jie Qi, Shunan Pang

      Pages 30-39

   5. Fast Forward RBF Network Construction Based on Particle Swarm Optimization

      • Jing Deng, Kang Li, George W. Irwin, Minrui Fei

      Pages 40-48

   6. A Modified Binary Differential Evolution Algorithm

      • Ling Wang, Xiping Fu, Muhammad Ilyas Menhas, Minrui Fei

      Pages 49-57

   7. Research on Situation Assessment of UCAV Based on Dynamic Bayesian Networks in Complex Environment

      • Lu Cao, An Zhang, Qiang Wang

      Pages 58-68

   8. Optimal Tracking Performance for Unstable Processes with NMP Zeroes

      • Jianguo Wang, Shiwei Ma, Xiaowei Gou, Ling Wang, Li Jia

      Pages 69-74

   9. Typhoon Cloud Image Enhancement by Differential Evolution Algorithm and Arc-Tangent Transformation

      • Bo Yang, Changjiang Zhang

      Pages 75-83

   10. Data Fusion-Based Extraction Method of Energy Consumption Index for the Ethylene Industry

       • Zhiqiang Geng, Yongming Han, Yuanyuan Zhang, Xiaoyun Shi

       Pages 84-92

   11. Research on Improved QPSO Algorithm Based on Cooperative Evolution with Two Populations

       • Longhan Cao, Shentao Wang, Xiaoli Liu, Rui Dai, Mingliang Wu

       Pages 93-100

   12. Optimum Distribution of Resources Based on Particle Swarm Optimization and Complex Network Theory

       • Li-lan Liu, Zhi-song Shu, Xue-hua Sun, Tao Yu

       Pages 101-109

   13. The Model of Rainfall Forecasting by Support Vector Regression Based on Particle Swarm Optimization Algorithms

       • Shian Zhao, Lingzhi Wang

       Pages 110-119

   14. Constraint Multi-objective Automated Synthesis for CMOS Operational Amplifier

       • Jili Tao, Xiaoming Chen, Yong Zhu

       Pages 120-127

   15. Research on APIT and Monte Carlo Method of Localization Algorithm for Wireless Sensor Networks

       • Jia Wang, Fu Jingqi

       Pages 128-137

   16. Quantum Immune Algorithm and Its Application in Collision Detection

       • Jue Wu, LingXi Peng, LiXue Chen, Lei Yang

       Pages 138-147

   17. An Artificial Bee Colony with Random Key for Resource-Constrained Project Scheduling

       • Yan-jun Shi, Fu-Zhen Qu, Wang Chen, Bo Li

       Pages 148-157

3. The Second Section: Advanced Neural Network and Fuzzy System Theory and Algorithms

   1. Combined Electromagnetism-Like Mechanism Optimization Algorithm and ROLS with D-Optimality Learning for RBF Networks

      • Fang Jia, Jun Wu

      Pages 158-165

   2. Stochastic Stability and Bifurcation Analysis on Hopfield Neural Networks with Noise

      • Xuewen Qin, Zaitang Huang, Weiming Tan

      Pages 166-179

The 2010 International Conference on Life System Modeling and Simulation (LSMS 2010) and the 2010 International Conference on Intelligent Computing for Sustainable Energy and Environment (ICSEE 2010) were formed to bring together researchers and practitioners in the fields of life system modeling/simulation and intelligent computing applied to worldwide sustainable energy and environmental applications. A life system is a broad concept, covering both micro and macro components ra- ing from cells, tissues and organs across to organisms and ecological niches. To c- prehend and predict the complex behavior of even a simple life system can be - tremely difficult using conventional approaches. To meet this challenge, a variety of new theories and methodologies have emerged in recent years on life system modeling and simulation. Along with improved understanding of the behavior of biological systems, novel intelligent computing paradigms and techniques have emerged to h- dle complicated real-world problems and applications. In particular, intelligent c- puting approaches have been valuable in the design and development of systems and facilities for achieving sustainable energy and a sustainable environment, the two most challenging issues currently facing humanity. The two LSMS 2010 and ICSEE 2010 conferences served as an important platform for synergizing these two research streams.

• biological simulation
• biological systems
• biomedical imaging
• biomedical signal processing
• biomedical visualization
• collective behavior
• distributed power generation
• evolutionary algorithms
• evolutionary computing
• life systems
• neural networks
• power
• algorithm analysis and problem complexity

• Electrical Engineering and Computer Science, The Queen’s University, Belfast, UK

  Kang Li

• School of Mechatronical Engineering and Automation, Shanghai University, Shanghai, China

  Minrui Fei, Li Jia

• School of Electronics, Electrical Engineering and Computer Science, The Queen’s University, Belfast, UK

  George W. Irwin

Policies and ethics