CSE 4138 : Soft Computing Lab

Course Overview

CSE 4138: Soft Computing Lab explores computational techniques that model and solve complex real-world problems using soft computing paradigms.
Sessions Conducted:

• Fall 2023, Spring 2024

Syllabus Highlights

1. Fuzzy Sets and Logic

   • Concepts and properties of fuzzy sets
   • Mathematical and logical implications of fuzzy sets
   • Fuzzy relations
   • Applications in information processing, decision making, and control systems

2. Artificial Neural Networks (ANNs)

   • Fundamental ideas and concepts of ANNs
   • Types: Feed-Forward, Recurrent, and others
   • Training rules and methodologies
   • Learning algorithms: error backpropagation, recurrent backpropagation

3. Probabilistic Reasoning

   • Bayesian inference models and Bayesian networks
   • Dempster–Shafer theory
   • Probabilistic decision support systems

4. Genetic Algorithms (GAs)

   • Principles and fundamental operators of GAs
   • GA-based search, optimization, learning, and control

5. Combined Approaches

   • Introduction to neuro-fuzzy-probabilistic-genetic combined approaches in computing applications