JNTUH B.Tech 4th Year 1 sem Computer Science and Engineering R13 (4-1) Soft Computing (Elective – II) R13 syllabus.

JNTUH B.Tech 4th year (4-1) Soft Computing gives you detail information of Soft Computing (Elective – II) R13 syllabus It will be help full to understand you complete curriculum of the year.

Objectives

• To give students knowledge of soft computing theories fundamentals, i.e. Fundamentals of artificial and neural networks, fuzzy sets and fuzzy logic and genetic algorithms.

UNIT-I

Al Problems and Search: Al problems, Techniques, Problem Spaces and Search, Heuristic Search Techniques- Generate and Test, Hill Climbing, Best First Search Problem reduction, Constraint Satisfaction and Means End Analysis. Approaches to Knowledge Representation- Using Predicate Logic and Rules.

UNIT-II

Artificial Neural Networks: Introduction, Basic models of ANN, important terminologies, Supervised Learning Networks, Perceptron Networks, Adaptive Linear Neuron, Back propagation Network. Associative Memory Networks. Traing Algorithms for pattern association, BAM and Hopfield Networks.

UNIT-III

Unsupervised Learning Network- Introduction, Fixed Weight Competitive Nets, Maxnet, Hamming Network, Kohonen Self-Organizing Feature Maps, Learning Vector Quanitizatton, Counter Propagation Networks, Adaptive Resonance Theory Networks. Special Networks-Introduction to various networks.

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TEXT BOOKS

• Principles of Soft Computing- S N Sivanandam, S N Deepa, Wiley India, 2007.
• Soft Computing and Intelligent System Design -Fakhreddine 0 Karray, Clarence D Silva, Pearson Edition, 2004.

REFERENCE BOOKS

• Artificial Intelligence and Soft Computing- Behavioural and Cognitive Modelling of the Human Brain- Amit Konar, CRC press, Taylor and Francis Group.
• Artificial Intelligence — Elaine Rich and Kevin Knight, TMH, 1991,rp2008.
• Artificial Intelligence — Patric Henry Winston — Third Edition, Pearson Education.
• A first course in Fuzzy Logic-Hung T Nguyen and Elbert A Walker, CRC. Press Taylor and Francis Group.
• Artificial Intelligence and Intelligent Systems, N.P.Padhy, Oxford Univ. Press.

Outcomes

• Student can able to building intelligent systems through soft computing techniques.
• Student should be able to understand the concept of artificial neural networks, fuzzy arithmetic and fuzzy logic with their day to day applications.

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