Applied Soft Computing Eie 6th Sem Syllabus for BE 2017 Regulation Anna Univ (Professional Elective II) detail syllabus for Electronics & Instrumentation Engineering (Eie), 2017 regulation is collected from the Anna Univ official website and presented for students of Anna University. The details of the course are: course code (EE8071), Category (PE), Contact Periods/week (3), Teaching hours/week (3), Practical Hours/week (0). The total course credits are given in combined syllabus.
For all other eie 6th sem syllabus for be 2017 regulation anna univ you can visit Eie 6th Sem syllabus for BE 2017 regulation Anna Univ Subjects. For all other Professional Elective II subjects do refer to Professional Elective II. The detail syllabus for applied soft computing is as follows.
Course Objective:
- To expose the students to the concepts of feed forward neural networks.
- To provide adequate knowledge about feedback neural networks
- To provide adequate knowledge about fuzzy and neuro-fuuzy systems
- To provide comprehensive knowledge of fuzzy logic control to real time systems.
- To provide adequate knowledge of genetic algorithms and its application to economic dispatch and unit commitment problems.
Unit I
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Unit II
Neural Networks for Control
Feedback networks – Discrete time Hopfield networks – Transient response of continuous time system – Applications of artificial neural network – Process identification – Neuro controller for inverted pendulum.
Unit III
Fuzzy Systems
Classical sets – Fuzzy sets – Fuzzy relations – Fuzzification – Defuzzification – Fuzzy rules -Membership function – Knowledge base – Decision-making logic – Introduction to neuro fuzzy system- Adaptive fuzzy system.
Unit IV
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Unit V
Genetic Algorithms
Basic concept of Genetic algorithm and detail algorithmic steps-adjustment of free Parameters-Solution of typical control problems using genetic algorithm- Concept on some other search techniques like tabu search and ant colony search techniques for solving optimization problems.
Course Outcome:
- Ability to understand and apply basic science, circuit theory, Electro-magnetic field theory control theory and apply them to electrical engineering problems.
- To understand and apply computing platform and software for engineering problems.
Text Books:
- Laurance Fausett, Englewood Cliffs, N.J., Fundamentals of Neural Networks, Pearson Education, 1992.
- Timothy J. Ross, Fuzzy Logic with Engineering Applications, Tata McGraw Hill, 3rdEdition , 2010..
- S.N.Sivanandam and S.N.Deepa, Principles of Soft computing, Wiley India Edition, 2nd Edition, 2013
References:
- Simon Haykin, Neural Networks, Pearson Education, 2003.
- John Yen and Reza Langari, Fuzzy Logic-Intelligence Control and Information, Pearson Education, New Delhi, 2003.
- M.Gen and R,Cheng, Genetic algorithms and optimization, Wiley Series in Engineering Design and Automation, 2000.
- Hagan, Demuth, Beale, Neural Network Design, Cengage Learning, 2012.
- N.P.Padhy, Artificial Intelligence and Intelligent Systems, Oxford, 2013.
- William S.Levine, Control System Advanced Methods, The Control Handbook CRC Press 2011.
For detail syllabus of all other subjects of BE Eie, 2017 regulation do visit Eie 6th Sem syllabus for 2017 Regulation.
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