Soft Computing Methods and Applications
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Follow on Instagram for UpdatesSoft Computing Methods and Applications Syllabus — Unit-wise Content
The official GTU curriculum for Soft Computing Methods and Applications (subject code 3734705) as prescribed for M · Semester 3 divides the course into 4 units, covering 27 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (3734705)Unit 1 Introduction to Soft Computing
- Importance of Soft Computing
- Main Components of Soft Computing
- Fuzzy Logic
- Artificial Neural Networks
- Support Vector machine
- Evolutionary Algorithms
- Hybrid Intelligent Systems
Unit 2 Fuzzy Logic Systems
- Introduction to Fuzzy logic
- classical sets vs fuzzy sets
- Features of membership functions
- Properties and operations on Fuzzy sets
- Fuzzy relation
- Operations of Fuzzy relation
- Fuzzy rule base and approximate reasoning
- Design a fuzzy logic controller: Mamdani & Sugeno Architecture
- Fuzzy logic control systems
Unit 3 Neural Network Systems
- Introduction to artificial neural network
- Biological neurons vs artificial neural network
- Neuron models
- Network architectures
- Learning in neural networks
- Back propagation network
- Hopfield network
- Self-organizing feature maps
- Control systems with neural networks
Unit 4 Applications of soft computing
- Applications of Fuzzy logic and neural network systems in automation
- robotics and machine vision. 4 Subject Code: 3734705 w.e.f
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