Significance of Hybrid Evolutionary Computation for Ab Initio Protein Folding Prediction

Houqe, Tamjid; Chetty, Madhu and Dooley, Laurence S. (2007). Significance of Hybrid Evolutionary Computation for Ab Initio Protein Folding Prediction. In: Grosan, Crina; Abraham, Ajith and Ishibuchi, Hisao eds. Hybrid Evolutionary Algorithms. Studies in Computational Intelligence Series (SCI), 75 (XVI). USA: Springer, pp. 235–256.

URL: http://www.springer.com/engineering/book/978-3-540...

Abstract

About the book:
Hybridization of evolutionary algorithms is getting popular due to their capabilities in handling several real world problems involving complexity, noisy environment, imprecision, uncertainty and vagueness. This edited volume is targeted to present the latest state-of-the-art methodologies in ’Hybrid Evolutionary Algorithms’. This book deals with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. This volume comprises of 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.

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About

• Item ORO ID
• 10535
• Item Type
• Book Section
• ISBN
• 3-540-73296-9, 978-3-540-73296-9
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Research Group
• Centre for Research in Computing (CRC)
• Depositing User
• Laurence Dooley