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Life System Modeling and Intelligent Computing

International Conference on Life System Modeling and Simulation, LSMS 2010, and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, Wuxi, China, September 17-20, 2010, Proceedings, Part II

  • Conference proceedings
  • © 2010

Overview

Part of the book series: Communications in Computer and Information Science (CCIS, volume 98)

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Table of contents (34 papers)

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

  2. The Second Section: Advanced Neural Network Theory and Algorithms

Keywords

About this book

The 2010 International Conference on Life System Modeling and Simulation (LSMS 2010) and the 2010 International Conference on Intelligent Computing for Susta- able Energy and Environment (ICSEE 2010) were formed to bring together resear- ers 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 mod- ing 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.

Editors and Affiliations

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

    Kang Li, George W. Irwin

  • Shanghai University, China

    Xin Li, Shiwei Ma

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