AKTU Application of Soft Computing (BCS056) Notes & Study Material PDF – B.Tech 3rd Year Sem 5

This 180-page study material provides topic-wise, in-depth coverage of the complete five-unit BCS-056 syllabus, with diagrams, solved numericals, important questions and an AKTU-pattern sample question paper.

🎓 Course Details

• Subject: Application of Soft Computing
• Course Code: BCS-056
• Year: 3rd Year
• Semester: V
• Course Type: Departmental Elective-II
• Credits: 3
• Branches: CSE / Computer Science / Computer Engineering / Allied Branches
• Syllabus Coverage: Complete 5 Units

🔹 UNIT I – Neural Networks-I: Introduction & Architecture

Topics include:

• Biological Neuron
• Nerve Structure & Synapse
• Artificial Neuron & Its Model
• Activation Functions
• Single-Layer Feedforward Networks
• Multilayer Feedforward Networks
• Recurrent Networks
• Learning Techniques
• Perceptron & Convergence Rule
• Auto-Associative Memory
• Hetero-Associative Memory

The PDF also contains worked examples involving McCulloch-Pitts neurons, perceptron weight updates and associative-memory weight matrices.

🔹 UNIT II – Neural Networks-II: Back Propagation Networks

Covers:

• Perceptron Model
• Single-Layer Artificial Neural Network
• Multilayer Perceptron
• Back Propagation Learning
• Back Propagation Algorithm
• Effect of Learning Rule Coefficient
• Factors Affecting Backpropagation Training
• Applications of Backpropagation Networks

🔹 UNIT III – Fuzzy Logic-I: Introduction

Includes:

• Basic Concepts of Fuzzy Logic
• Fuzzy Sets & Crisp Sets
• Fuzzy Set Theory
• Fuzzy Set Operations
• Properties of Fuzzy Sets
• Fuzzy Relations
• Crisp Relations
• Fuzzy-to-Crisp Conversion

🔹 UNIT IV – Fuzzy Logic-II: Membership & Rules

Topics include:

• Membership Functions
• Inference in Fuzzy Logic
• Fuzzy If-Then Rules
• Fuzzy Implications
• Fuzzy Algorithms
• Fuzzification
• Defuzzification
• Fuzzy Controllers
• Industrial Applications of Fuzzy Logic

🔹 UNIT V – Genetic Algorithms

Covers:

• Basic Concepts of Genetic Algorithms
• Working Principle
• GA Procedure
• GA Flowchart
• Genetic Representation / Encoding
• Initialization
• Selection
• Genetic Operators
• Crossover
• Mutation
• Generational Cycle
• Applications of Genetic Algorithms