Download WordPress Themes, Happy Birthday Wishes
Home » Computer » Genetic Algorithms in Applications

Genetic Algorithms in Applications

  • Category: Computer
  • Author: Rustem Popa
  • Pages: 328 pages
  • File type: PDF Files, and an zipped PDF, 5.85 MB

Read and download free eBook intituled Genetic Algorithms in Applications in format PDF Files, and an zipped PDF, 5.85 MB – 328 pages created by Rustem Popa.

This well-organized book takes the reader through the new and rapidly expanding field of genetic algorithms step by step, from a discussion of numerical optimization, to a survey of current extensions to genetic algorithms and applications.

Genetic Algorithms (GAs) are one of several techniques in the family of Evolutionary Algorithms – algorithms that search for solutions to optimization problems by “evolving” better and better solutions. Genetic Algorithms have been applied in science, engineering, business and social sciences.

This book consists of 16 chapters organized into five sections. The first section deals with some applications in automatic control, the second section contains several applications in scheduling of resources, and the third section introduces some applications in electrical and electronics engineering. The next section illustrates some examples of character recognition and multi-criteria classification, and the last one deals with trading systems. These evolutionary techniques may be useful to engineers and scientists in various fields of specialization, who need some optimization techniques in their work and who may be using Genetic Algorithms in their applications for the first time. These applications may be useful to many other people who are getting familiar with the subject of Genetic Algorithms.

Read and Download Links:

Genetic Algorithms in Applications

READ  Basics of Compiler Design

Leave a Reply

Your email address will not be published. Required fields are marked *



Check Also

The Linux Command Line

Read and download free Book intituled The Linux Command Line in format PDF written by William Shotts.