IT

CCS364: Soft Computing syllabus for IT 2021 regulation (Professional Elective-VII)

Soft Computing detailed syllabus for Information Technology (IT) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the IT students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.

For Information Technology 6th Sem scheme and its subjects, do visit IT 6th Sem 2021 regulation scheme. For Professional Elective-VII scheme and its subjects refer to IT Professional Elective-VII syllabus scheme. The detailed syllabus of soft computing is as follows.

Soft Computing

Course Objectives:

Download the iStudy App for all syllabus and other updates.
Get it on Google Play

Unit I

INTRODUCTION TO SOFT COMPUTING AND FUZZY LOGIC 6 Introduction – Fuzzy Logic – Fuzzy Sets, Fuzzy Membership Functions, Operations on Fuzzy Sets, Fuzzy Relations, Operations on Fuzzy Relations, Fuzzy Rules and Fuzzy Reasoning, Fuzzy Inference Systems

Unit II

Download the iStudy App for all syllabus and other updates.
Get it on Google Play

Unit III

GENETIC ALGORITHMS 6 Chromosome Encoding Schemes -Population initialization and selection methods – Evaluation function – Genetic operators- Cross over – Mutation – Fitness Function – Maximizing function

Unit IV

Download the iStudy App for all syllabus and other updates.
Get it on Google Play

Unit V

APPLICATIONS 6 Modeling a two input sine function – Printed Character Recognition – Fuzzy filtered neural networks – Plasma Spectrum Analysis – Hand written neural recognition – Soft Computing for Color Recipe Prediction.

Course Outcomes:

Download the iStudy App for all syllabus and other updates.
Get it on Google Play

Practical Exercises

  1. Implementation of fuzzy control/ inference system
  2. Programming exercise on classification with a discrete perceptron
  3. Implementation of XOR with backpropagation algorithm
  4. Implementation of self organizing maps for a specific application
  5. Programming exercises on maximizing a function using Genetic algorithm
  6. Implementation of two input sine function
  7. Implementation of three input non linear function

Text Books:

  1. SaJANG, J.-S. R., SUN, C.-T., & MIZUTANI, E. (1997). Neuro-fuzzy and soft computing: A computational approach to learning and machine intelligence. Upper Saddle River, NJ, Prentice Hall,1997
  2. Himanshu Singh, Yunis Ahmad Lone, Deep Neuro-Fuzzy Systems with Python
  3. With Case Studies and Applications from the Industry, Apress, 2020

Reference Books:

Download the iStudy App for all syllabus and other updates.
Get it on Google Play

For detailed syllabus of all the other subjects of Information Technology 6th Sem, visit IT 6th Sem subject syllabuses for 2021 regulation.

For all Information Technology results, visit Anna University IT all semester results direct link.

Leave a Reply

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

*