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B.Tech. IV (CO) Semester - 8

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CO410 : SOFT COMPUTING (ELECTIVE-I)

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COURSE OBJECTIVES
  • Introduce students to soft computing concepts and techniques and foster their abilities in designing and implementing soft computing based solutions for real-world and engineering problems.
  • Introduce students to fuzzy systems, fuzzy logic and its applications.
  • Explain the students about Artificial Neural Networks and various categories of ANN.
COURSE OUTCOMES
After successful completion of this course, student will be able to
  • Understand soft computing techniques and their role in problem solving.
  • Conceptualize and parameterize various problems to be solved through basic soft computing techniques.
  • Analyze and integrate various soft computing techniques in order to solve problems effectively and efficiently.
COURSE CONTENT
  • INTRODUCTION TO SOFT COMPUTING

    • (06 Hours)

    Fuzzy Computing, Neural Computing, Genetic Algorithms, Associative Memory, Adaptive Resonance Theory, Applications
  • FUNDAMENTALS OF NEURAL NETWORK

    • (06 Hours)

    Model of artificial neuron, architectures, learning models, single layer NNs, multi layer NNs, back propagation networks
  • ASSOCIATIVE MEMORY

    • (04 Hours)

    Auto-associative memory, bi-directional hetero-associative memory
  • FUZZY SET THEORY

    • (06 Hours)

    Fuzzy sets, membership, operations, properties, fuzzy relation
  • FUZZY SYSTEMS

    • (02 Hours)

    Fuzzy logic, fuzzification, fuzzy inference, fuzzy rule based system
  • FUNDAMENTAL OF GENETIC ALGORITHMS

    • (06 Hours)

    Encoding, operations of GA
  • NATURE INSPIRED OPTIMIZATION TECHNIQUES

    • (04 Hours)

    Ant Colony, particle swarm optimization
  • HYBRID SYSTEM

    • (04 Hours)

    Integrating Neural networks, fuzzy logic, and genetic algorithms, GA based back propagation networks, fuzzy back propagation networks
  • ADVANCED TOPICS

    • (04 Hours)

    (Total Contact Time: 42 Hours)
    BOOKS RECOMMENDED

    1. Hoffmann, F., Koeppen, M., Klawonn, F., Roy, R: "Soft Computing: Methodologies and Applications", Springer, 2005
    2. S. N. Sivanandam & S.N. Deepa, "Principles of Soft Computing", Wiley, 2007
    3. Rafik Aziz oglyAliev, R. R. Aliev: "Soft Computing and Its Applications", World Scientific, 2001
    4. S. Rajasekaran, G. A. Vijayalakshmi Pai, "Neural Networks, Fuzzy Logic And Genetic Algorithm: Synthesis And Applications", Phi, 2003
    5. David E. Goldberg, "Genetic Algorithms", Pearson Education India, 2006
    6. B. Yagnanarayana, "Artificial Neural Networks", PHI, 2009
    7. Simon O. Haykin, "Neural Networks and Learning Machines", 3/E, Prentice Hall, 2009