Course

Computational intelligence (CI): Adaptation, Self-organization and Evolution, Biological and artificial neuron, Neural Networks Concepts, Paradigms, Implementations, Evolutionary computing: Concepts, Paradigms, Implementation, Swarm Intelligence, Artificial Immune Systems, Fuzzy systems: Concepts, Paradigms, Implementation, Hybrid systems, CI application: case studies may include sensor networks, digital systems, control, forecasting and time-series predictions.

Learning Objectives

LO1    To introduce the principles of Computational Intelligence technique.

LO2    To provide insights on the various CI paradigms

LO3    To impart knowledge to select a suitable CI principle to solve engineering or real-life
problems.

Course Outcomes

CO1    Ability to understand concepts of basic principles of Computational Intelligence
techniques.

CO2    Ability to Understand various neural network architectures

CO3    Ability to analyse and define various fuzzy systems

CO4    Ability to design and implement suitable CI principle to solve engineering or real life.

CO-PO Mapping

Textbooks/References:

1. C. Eberhart, “Computational Intelligence: Concept to Implementations”, Morgan

Kaufmann Publishers, 2007.

2. A Konar, “Computational Intelligence: Principles, Techniques and Applications”,

Springer Verlag, 2005.