Teaching
CSE 4138 : Soft Computing Lab

CSE 4138 : Soft Computing Lab

Conducting this course since Fall 2023.

Syllabus:

  1. Fuzzy Sets and Logic:
    • Concepts and properties of fuzzy sets.
    • Mathematical and logical implications of fuzzy sets.
    • Fuzzy relations.
    • Applications of fuzzy sets in information processing, decision making, and control systems.
  2. Artificial Neural Networks (ANNs):
    • Underlying ideas and concepts of ANNs.
    • Types of ANNs: Feed-Forward, Recurrent, and others.
    • Rules and methodologies for training ANNs.
    • Learning algorithms, including error backpropagation and recurrent backpropagation.
  3. Probabilistic Reasoning:
    • Bayesian inference models and Bayesian networks.
    • Dempster–Shafer theory.
    • Probabilistic decision support systems.
  4. Genetic Algorithms (GAs):
    • Underlying principles and fundamental operators of GAs.
    • Searching based on GAs.
    • GA-based optimization, learning, and control.
  5. Combined Approaches:
    • Introduction to neuro-fuzzy-probabilistic-genetic combined approaches in computing applications.