Introduction to Soft Computing: Review of AI techniques and soft computing techniques & their applications in instrumentation engineering.

 

Multiobjective optimization:  Comparison with single objective optimization, Dominance ,Non Dominated shorting, Multiobjective optimization using GA.

 

Advanced AI Techniques: Swarm Intelligence (SI), Particle swarm optimization (PSO), Ant-Colony Optimization, Petrinets, Coloured-Petrinets, Entropy , Multi-agent and Hierarchical  applications of advanced AI techbniques in Control/ Signal processing/ Robotics.

 

Rough Set Theory: Introduction, Information system, Indiscernibility, Rough sets, Rough set theory, Set approximation, Rough membership, Attributes, Dependency of attributes, Rough equivalence, Reducts, Rough Reducts based on SVM, Hybrid set systems -Fuzzy rough sets, Topological structures of rough sets over fuzzy lattices, Fuzzy reasoning based on universal logic,

 

Granular Computing: Soft sets to information systems, Uses and applications of granular computing in instrumentation engineering.

 

Hybrid AI Techniques: Introduction to Hybrid AI systems : Neuro- Fuzzy, Fuzzy-rough set systems, Neuro-Fuzzy-GA systems and case studies around Hybrid systems.

 

Recommended Books

1. Duntsch,I and Gediga, G., Rough set data analysis: A Road to Non-invasive Knowledge Discovery, Methodos  Publishers (2006).
2. Klir, G. J., Yuan, Bo, Fuzzy Sets and Fuzzy Logic, Theory and Applications, Prentice-Hall of India Private Limited (2007).
3. Ross, T.J., Fuzzy Logic with Engineering Applications, Wiley (2004) 2^nd ed.