Soft Computing Techniques detailed syllabus for Electrical & Electronics Engineering (EEE) for 2019 regulation curriculum has been taken from the Anna Universities official website and presented for the EEE students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Electrical & Electronics Engineering 7th Sem scheme and its subjects, do visit EEE 7th Sem 2019 regulation scheme. For Professional Elective-V scheme and its subjects refer to EEE Professional Elective-V syllabus scheme. The detailed syllabus of soft computing techniques is as follows.
Course Objective:
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Unit I
Artificial Neural Network
Review of fundamentals – Biological neuron, artificial neuron, activation function, single layer perceptron – Limitation – Multi layer perceptron – Back propagation algorithm (BPA) – Recurrent neural network (RNN) – Adaptive resonance theory (ART) based network – Radial basis function network – online learning algorithms, BP through time – RTRL algorithms – Reinforcement learning.
Unit II
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Unit III
Fuzzy Set Theory
Fuzzy set theory – Fuzzy sets – Operation on fuzzy sets – Scalar cardinality, fuzzy cardinality, union and intersection, complement (Yager and Sugeno), equilibrium points, aggregation, projection, composition, cylindrical extension, fuzzy relation – Fuzzy membership functions
Unit IV
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Unit V
Hybrid Control Schemes
Fuzzification and rule base using ANN – Neuro fuzzy systems – ANFIS – Fuzzy neuron- Introduction to GA – Optimization of membership function and rule base using Genetic Algorithm – Introduction to support vector machine – Particle swarm optimization – Case study – Familiarization with ANFIS toolbox
Course Outcome:
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
Text Books:
- Laurence Fausett, “Fundamentals of Neural Networks”, Prentice Hall, Englewood Cliffs, N.J., 1992.
- Timothy J. Ross, “Fuzzy Logic with Engineering Applications”, McGraw Hill Inc., 2000.
References:
- Goldberg, “Genetic Algorithm in Search, Optimization and Machine learning”, Addison Wesley Publishing Company Inc. 1989
- Millon W.T., Sutton R.S. and Webrose P.J., “Neural Networks for Control”, MIT press, 1992
- EthemAlpaydin, “Introduction to Machine learning (Adaptive Computation and Machine Learning series)”, MIT Press, Second Edition, 2010.
- Zhang Huaguang and Liu Derong, “Fuzzy Modeling and Fuzzy Control Series: Control Engineering”, 200
For detailed syllabus of all the other subjects of Electrical & Electronics Engineering 7th Sem, visit EEE 7th Sem subject syllabuses for 2019 regulation.
For all Electrical & Electronics Engineering results, visit Anna University EEE all semester results direct link.