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Design and Analysis of Algorithms by Himanshu B. Dave, Parag H. Dave

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Chapter 13

Natural Algorithms — GA, SA, ANN, TS

Objectives

After reading this chapter, you should understand:

  • Why do we need Natural Algorithms — Where traditional algorithm design strategies fail
  • Evolution
  • Mutation and its significance
  • Working of a Genetic Algorithm — Why they work, how do they differ from random search
  • Simulated Annealing — Principles and applicability
  • Artificial Neural Networks — Similarities and differences with Human Brain
  • Artificial Neural Networks — Types, principles and applicability
  • A single Artificial Neuron — How it processes inputs
  • Electronic Implementation of Artificial Neural Networks
  • Supervised and Unsupervised learning : Differences
  • Training an ANN — The Why and How
  • Differences between ANN and Traditional Computing ...

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