In the name of of Allah the Merciful

Nature-Inspired Algorithms: For Engineers and Scientists

Krishn Kumar Mishra, B0BDBGNXPF, 036775049X, 2022009541, 2022009542, 9780367750497, 9781000637595, 9781000637632, 9781032322643, 9781003313649, 978-0367750497, 978-1000637595, 978-1000637632, 978-1032322643, 978-1003313649

70,000 Toman
The desired product is not available.

English | 2022 | PDF

تعداد
نوع
  • {{value}}
کمی صبر کنید...

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 
  • Examines  well-known algorithms like the genetic algorithm, particle swarm  optimization and differential evolution, and recent approaches like gray  wolf optimization.
  • Provides conceptual linking of algorithms with theoretical concepts 

The  text will be useful for graduate students in the field of electrical  engineering, electronics engineering, computer science and engineering. 

Discussing  nature inspired algorithms and their applications in a single volume,  this text will be useful as a reference text for graduate students in  the field of electrical engineering, electronics engineering, computer  science and engineering. It discusses important algorithms including  deterministic algorithms, randomized algorithms, evolutionary  algorithms, particle swarm optimization, big bang big crunch (BB-BC)  algorithm, genetic algorithm and grey wolf optimization algorithm. "