MC4006 Soft Computing Techniques Syllabus:
MC4006 Soft Computing Techniques Syllabus – Anna University PG Syllabus Regulation 2021
COURSE OBJECTIVES:
To gain knowledge of soft computing theories and its fundamentals.
To design a soft computing system required to address a computational task.
To learn and apply artificial neural networks, fuzzy sets and fuzzy logic and genetic algorithms in problem solving and use of heuristics based on human experience.
To introduce the ideas of fuzzy sets, fuzzy logic and to become familiar with neural networks that can learn from available examples and generalize to form appropriate rules for inferencing systems.
To familiarize with genetic algorithms and other random search procedures while seeking global optimum in self – learning situations
UNIT I FUZZY COMPUTING
Basic Concepts of Fuzzy Logic, Fuzzy Sets and Crisp Sets, Fuzzy Set Theory and Operations, Properties of Fuzzy Sets, Fuzzy and Crisp Relations, Fuzzy to Crisp Conversion Membership Functions, Interference in Fuzzy Logic, Fuzzy If – Then Rules, Fuzzy Implications and Fuzzy Algorithms, Fuzzification and Defuzzification, Fuzzy Controller, Industrial Applications.
UNIT II FUNDAMENTALS OF NEURAL NETWORKS
Neuron, Nerve Structure and Synapse, Artificial Neuron and its Model, Activation Functions, Neural Network Architecture: Single Layer and Multilayer Feed Forward Networks, Recurrent Networks. Various Learning Techniques; Perception and Convergence Rule, Auto-Associative and Hetero-Associative Memory
UNIT III BACKPROPAGATION NETWORKS
Back Propagation Networks) Architecture: Perceptron Model, Solution, Single Layer Artificial Neural Network, Multilayer Perceptron Model; Back Propagation Learning Methods, Effect of Learning Rule Co – Efficient ;Back Propagation Algorithm, Factors Affecting Backpropagation Training, Applications
UNIT IV COMPETITIVE NEURAL NETWORKS
Kohenen’s Self Organizing Map – SOM Architecture, learning procedure – Application; Learning Vector Quantization – learning by LVQ; Adaptive Resonance Theory – Learning procedure – Applications.
UNIT V GENETIC ALGORITHM
Basic Concepts, Working Principle, Procedures of GA, Flow Chart of GA, Genetic Representations, (Encoding) Initialization and Selection, Genetic Operators, Mutation, Generational Cycle, Applications
TOTAL: 45 PERIODS
SUGGESTED ACTIVITIES:
Prepare a weekly timetable for classes in a college for different groups of students so that there are no clashes between classes. The task is to search for the optimum using GA
Species identification of a plant using Back propagation Algorithm
Bandwidth allocation for wireless system using Neural network
Apply Fuzzy logic for washing machines to determine the correct amount of water and detergent, speed of agitation, and length of the wash cycles.
Apply Fuzzy logic for breast cancer diagnosis
Do a Case Study Effect of Road Traffic Noise Pollution on Human Work Efficiency in Offices/ Organizations/ Commercial Business Centers in cities Using Fuzzy Expert System:
COURSE OUTCOMES:
On completion of the course, the students will be able to:
CO1: Identify and describe soft computing techniques and their roles in building intelligent machines.
CO2: Recognize the feasibility of applying a soft computing methodology for a particular problem.
CO3: Apply fuzzy logic and reasoning to handle uncertainty and solve engineering problems.
CO4: Apply genetic algorithms to optimization problems.
CO5: Design neural networks to pattern classification and regression problems using a soft computing approach.
REFERENCES
1. J.S.R. Jang, C.T. Sun and E. Mizutani, “Neuro – Fuzzy and Soft Computing”, Pearson Education, 2004.
2. S. Rajasekaran and G.A. Vijayalakshmi Pai, “Neural Networks, Fuzzy Systems and Evolutionary Algorithms: Synthesis and Applications”, PHI Learning, 2nd Edition, 2017.
3. S. N. Sivanandam, S. N. Deepa, “Principles of Soft Computing”, Third Edition, Wiley, 2018.
4. Simon Haykin, “Neural Networks and Learning Machines”, Pearson, 3rd Edition, 2009.
5. Timothy Ross, “Fuzzy Logic with Engineering Applications”, Wiley Publications, 4th Edition 2016.