AI Techniques in Electrical Engineering detailed syllabus for Electrical & Electronics Engineering (EEE), R18 regulation has been taken from the JNTUHs official website and presented for the students of B.Tech Electrical & Electronics Engineering branch affiliated to JNTUH course structure. For Course Code, Course Titles, Theory Lectures, Tutorial, Practical/Drawing, Credits, and other information do visit full semester subjects post given below. The syllabus PDF files can also be downloaded from the universities official website.
For all the other EEE 4th Year 2nd Sem Syllabus for B.Tech R18 Regulation JNTUH scheme, visit Electrical & Electronics Engineering 4th Year 2nd Sem R18 Scheme.
For all the (Professional Elective-5) subjects refer to Professional Elective-5 Scheme. The detail syllabus for ai techniques in electrical engineering is as follows.
Pre-requisites:
Power Systems Operation and Control
Course Objective:
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Course Outcome:
Upon the completion of this course, the student will be able to
- Understand feed forward neural networks, feedback neural networks and learning techniques.
- Understand fuzziness involved in various systems and fuzzy set theory.
- Develop fuzzy logic control for applications in electrical engineering
- Develop genetic algorithm for applications in electrical engineering.
Unit – I
Artificial Neural Networks: Introduction, Models of Neuron Network-Architectures -Knowledge representation, Artificial Intelligence and Neural networks-Learning process -Error correction learning, Hebbian learning -Competitive learning-Boltzman learning, supervised learning-Unsupervised learning-Reinforcement learning-Learning tasks.
Unit – II
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Unit – III
Fuzzy Logic: Introduction -Fuzzy versus crisp, Fuzzy sets-Membership function -Basic Fuzzy set operations, Properties of Fuzzy sets -Fuzzy Cartesian Product, Operations on Fuzzy relations -Fuzzy logic-Fuzzy Quantifiers, Fuzzy Inference-Fuzzy Rule based system, Defuzzification methods.
Unit – IV
Genetic Algorithms: Introduction-Encoding -Fitness Function-Reproduction operators, Genetic Modeling -Genetic operators-Cross over-Single site cross over, Two point cross over -Multi point cross over Uniform cross over, Matrix cross over-Cross over Rate-Inversion and Deletion, Mutation operator -Mutation -Mutation Rate-Bit-wise operators, Generational cycle-convergence of Genetic Algorithm.
Unit – V
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
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Text Books:
- S. Rajasekaran and G.A.V. Pai Neural Networks, Fuzzy Logic and Genetic Algorithms, PHI, New Delhi, 2003.
- Rober J. Schalkoff, Artificial Neural Networks, Tata McGraw Hill Edition, 2011.
Reference Books:
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..
For detail syllabus of all other subjects of B.Tech Electrical & Electronics Engineering 4th Year 2nd Sem , visit EEE 4th Year 2nd Sem syllabus subjects.
For B.Tech Electrical & Electronics Engineering (EEE) 4th Year results, visit JNTUH B.Tech Electrical & Electronics Engineering semester results direct link.