Introduction To Soft Computing detail syllabus for Mechanical Engineering (ME), 2019-20 scheme is taken from AKTU official website and presented for AKTU students. The course code (KOE036), and for exam duration, Teaching Hr/Week, Practical Hr/Week, Total Marks, internal marks, theory marks, and credits do visit complete sem subjects post given below.
For all the other me 3rd sem syllabus for b.tech 2019-20 scheme aktu you can visit ME 3rd Sem syllabus for B.Tech 2019-20 Scheme AKTU Subjects. For all the other Select Subject-1 subjects do refer to Select Subject-1. The detail syllabus for introduction to soft computing is as follows.
Unit I
Introduction to Soft Computing, Artificial Neural Networks: Basic concepts-Single layer perception-Multi layer Perception-Supervised and Unsupervised learning-Back propagation networks-Kohnen’s self-organizing networks-Hopfield network.
Unit II
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Unit III
Neuro-Fuzzy Modelling: Adaptive networks based Fuzzy interface systems-Classification and Regression Trees-Data clustering algorithms-Rule based structure identification-Neuro-Fuzzy controls-Simulated annealing-Evolutionary computation.
Unit IV
Genetic Algorithms: Survival of the Fittest-Fitness Computations-Cross over-Mutation-Reproduction-Rank method-Rank space method.
Unit V
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Course Outcomes:
At the end of course, the student will be able to understand:
- Comprehend the fuzzy logic and the concept of fuzziness involved in various systems and fuzzy set theory.
- Understand the concepts of fuzzy sets, knowledge representation using fuzzy rules, approximate reasoning, fuzzy inference systems, and fuzzy logic.
- Describe with genetic algorithms and other random search procedures useful while seeking global optimum in self learning situations.
- Understand appropriate learning rules for each of the architectures and learn several neural network paradigms and its applications.
- Develop some familiarity with current research problems and research methods in Soft Computing Techniques.
Text Books:
- An Introduction to Genetic Algorithm Melanic Mitchell (MIT Press).
- Evolutionary Algorithm for Solving Multi-objective, Optimization Problems (2nd Edition), Collelo, Lament, Veldhnizer ( Springer).
- Fuzzy Logic with Engineering Applications Timothy J. Ross (Wiley).
- Neural Networks and Learning Machines Simon Haykin (PHI).
- Sivanandam, Deepa, Principles of Soft Computing, Wiley.
- Jang J.S.R, Sun C.T. and Mizutani E, “Neuro-Fuzzy and Soft computing”, Prentice Hall.
- Timothy J. Ross, “Fuzzy Logic with Engineering Applications”, McGraw Hill.
- Laurene Fausett, “Fundamentals of Neural Networks”, Prentice Hall.
- D.E. Goldberg, “Genetic Algorithms: Search, Optimization and Machine Learning”, Addison Wesley.
- Wang, Fuzzy Logic, Springer.
For the detailed syllabus of all the other subjects of B.Tech Me, 2019-20 regulation do visit Me 3rd Sem syllabus for 2019-20 Regulation.
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