Neural Network & Fuzzy logics Syllabus for Automation M.Tech first year first sem is covered here. This gives the details about credits, number of hours and other details along with reference books for the course.
The detailed syllabus for Neural Network & Fuzzy logics M.Tech 2017-2018 (R17) first year first sem is as follows.
M.Tech. I Year I Sem.
UNIT-I : Knowledge and Processing – Knowledge and Intelligence- logic frames- production systems. Fundamentals of Fuzzy logic-characteristics of fuzzy logic and systems-Fuzzy sets-Fuzzy number Equality of fuzzy sets- Empty Fuzzy set –Fuzzy point-universal Fuzzy set. Operations on Fuzzy sets Intersection-union –complement.
UNIT-II : Fuzzy Relations-classical N-Array Relation-Reflexivity-Anti reflexivity-symmetricity –Transitivity Equivalence-Binary fuzzy relations, operation on Fuzzy relations-Intersection-union-projectionCartesian product.
UNIT-III : Fuzzy Implications, Translation rules, Triangular norms, Triangular conorm, Fuzzy Rule base system, Fuzzy logic controller, Defuzzification Methods, Fuzzy logic applications-prevention of Road accidents-control room temperature-Robot control system-domestic applications-Industrial applications.
UNIT-IV : Basic concepts of Neural Network-Processing units-connection between units-output rules- Network topologies-paradigms of learning –perception, Back-propagation, classification Models-Association Models, optimization models.
UNIT-V : Rule Based Neural Networks-Network Training –Application of Neural Network in Mathematical Modeling- Knowledge based approaches-applications in Mechanical Engineering –Fuzzy –Neural, example, Neuro –Fuzzy examples-Intelligence in Automation.
REFERENCES:
- Fuzzy logic &Neural Networks/ Chennakesava R. Alavala/ New Age International, 2008
- Intelligent Control Fuzzy Logic Applications/ Clarence W.de Silva/ CRS Press, 1995.
- Fuzzy Logic with engineering Applications/ Timothy J. Ross/ McGraw Hill Inc., 1995.
- Neural Networks in Computer Intelligence/ Limin Fu / Tata McGraw Hill Publishing Company Ltd., 2003
- Stamations and Understanding Neural Networks and Fuzzy Logic/ V. Karthalopoulos Basic concepts Applications, IEE Neural Networks Council PHI 2001.
- Neural Networks Algorithms, Applications/ James A. Freeman and David M. Skapura & Programming Techniques/ Pearson Education Asia, 2001
- Artificial Neural Networks/ Yegnarayane. B/ Prentice Hall- 2001.
- N.P. Padhya & S.P. Simon, soft computing with MAT LAB Programming, Oxford University Press, 2015.
For all other M.Tech 1st Year 1st Sem syllabus go to JNTUH M.Tech Automation 1st Year 1st Sem Course Structure for (R17) Batch.
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