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Nature-Inspired Algorithms: For Engineers and Scientists [Paperback]

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  • Category: Books (Science)
  • Author:  Kumar Mishra, Krishn
  • Author:  Kumar Mishra, Krishn
  • ISBN-10:  1032322640
  • ISBN-10:  1032322640
  • ISBN-13:  9781032322643
  • ISBN-13:  9781032322643
  • Publisher:  CRC Press
  • Publisher:  CRC Press
  • Pages:  326
  • Pages:  326
  • Binding:  Paperback
  • Binding:  Paperback
  • SKU:  1032322640-11-MPOD
  • SKU:  1032322640-11-MPOD
  • Item ID: 107096267
  • Seller: ShopSpell
  • Ships in: 2 business days
  • Transit time: Up to 5 business days
  • Delivery by: Oct 11 to Oct 13
  • Notes: Brand New Item. Not shipped to AK, HI, APO, FPO, AE.

The text discusses nature inspired algorithms and their applications in a comprehensive manner. It will be an ideal reference text for graduate students in the field of electrical engineering, electronics engineering, computer science and engineering.

K. K. Mishra is presently working as an assistant professor, department of computer science and engineering, Motilal Nehru National Institute of Technology Allahabad, India. His research areas include genetic algorithm, analysis of algorithm, automata theory, microprocessor and multi-objective optimization. He has taught courses including computer architecture, data structures, advanced computer architecture, programming in C++, microprocessor and automata theory at undergraduate and graduate level. He is a regular reviewer of the Journal of Supercomputing (Springer), Applied Intelligence, Applied Soft Computing, IEEE Transaction on Cybernetics, IEEE System Journal, Neural computing and application, and IETE journals.This comprehensive reference text discusses nature inspired algorithms and their applications. It presents the methodology to write new algorithms with the help of MATLAB programs and instructions for better understanding of concepts. It covers well-known algorithms including evolutionary algorithms, genetic algorithm, particle Swarm optimization and differential evolution, and recent approached including gray wolf optimization. A separate chapter discusses test case generation using techniques such as particle swarm optimization, genetic algorithm, and differential evolution algorithm.

The book-

  • Discusses in detail various nature inspired algorithms and their applications
  • Provides MATLAB programs for the corresponding algorithm
  • Presents methodology to write new algorithms
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