Soft Computing

  • Computing & Information Technology |
  • English

Description

This course introduces soft computing methods which, unlike hard computing, are tolerant of imprecision, uncertainty and partial truth. The principal constituents of soft computing are fuzzy logic, neural network theory, and genetic algorithms.

Program

Computer Science

Objectives

  • 1. Understand the difference between hard and soft computing methods.
    2. Be able to apply several soft computing techniques for learning from experimental data.
    3. Understand what fuzzy logic is and apply it in various applications.
    4. Apply neural networks to solve soft computing problems
    5. Use genetic algorithms to solve soft computing problems.

Textbook

S. N. Sivanandam and S. N. Deepa, Principles of Soft Computing, WILEY

Course Content

content serial Description

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Courses
  • Degree Bachelor
  • Code: CS464
  • Credit hrs: 3
  • Prequisites: CS366
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