MC9296 SOFT COMPUTING SYLLABUS | ANNA UNIVERSITY MCA 5TH SEM SYLLABUS REGULATION 2009 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY FIFTH SEMESTER M.C.A. (MASTER OF COMPUTER APPLICATIONS) DEPARTMENT SYLLABUS, TEXTBOOKS, REFERENCE BOOKS,EXAM PORTIONS,QUESTION BANK,PREVIOUS YEAR QUESTION PAPERS,MODEL QUESTION PAPERS, CLASS NOTES, IMPORTANT 2 MARKS, 8 MARKS, 16 MARKS TOPICS. IT IS APPLICABLE FOR ALL STUDENTS ADMITTED IN THE YEAR 2011 2012-2013 (ANNA UNIVERSITY CHENNAI,TRICHY,MADURAI,TIRUNELVELI,COIMBATORE), 2009 REGULATION OF ANNA UNIVERSITY CHENNAI AND STUDENTS ADMITTED IN ANNA UNIVERSITY CHENNAI DURING 2009
MC9296 SOFT COMPUTING LT P C
3 0 0 3
UNIT I INTRODUCTION TO SOFT COMPUTING AND NEURAL NETWORKS 9
Evolution of Computing - Soft Computing Constituents – From Conventional AI to
Computational Intelligence - Machine Learning Basics
UNIT II GENETIC ALGORITHMS 9
Introduction to Genetic Algorithms (GA) – Applications of GA in Machine Learning -
Machine Learning Approach to Knowledge Acquisition.
UNIT III NEURAL NETWORKS 9
Machine Learning Using Neural Network, Adaptive Networks – Feed forward Networks –
Supervised Learning Neural Networks – Radial Basis Function Networks -
Reinforcement Learning – Unsupervised Learning Neural Networks – Adaptive
Resonance architectures – Advances in Neural networks.
UNIT IV FUZZY LOGIC 9
Fuzzy Sets – Operations on Fuzzy Sets – Fuzzy Relations – Membership Functions-
Fuzzy Rules and Fuzzy Reasoning – Fuzzy Inference Systems – Fuzzy Expert Systems
– Fuzzy Decision Making.
UNIT V NEURO-FUZZY MODELING 9
Adaptive Neuro-Fuzzy Inference Systems – Coactive Neuro-Fuzzy Modeling –
Classification and Regression Trees – Data Clustering Algorithms – Rulebase Structure
Identification – Neuro-Fuzzy Control – Case studies.
TOTAL : 45 PERIODS
44
TEXT BOOKS:
1. Jyh-Shing Roger Jang, Chuen-Tsai Sun, Eiji Mizutani, “Neuro-Fuzzy and Soft
Computing”, Prentice-Hall of India, 2003.
2. George J. Klir and Bo Yuan, “Fuzzy Sets and Fuzzy Logic-Theory and
Applications”,Prentice Hall, 1995.
3. James A. Freeman and David M. Skapura, “Neural Networks Algorithms,
Applications, and Programming Techniques”, Pearson Edn., 2003.
REFERENCES:
1. Mitchell Melanie, “An Introduction to Genetic Algorithm”, Prentice Hall, 1998.
2. David E. Goldberg, “Genetic Algorithms in Search, Optimization and Machine
Learning”, Addison Wesley, 1997.
3. S. N. Sivanandam, S. Sumathi and S. N. Deepa, “Introduction to Fuzzy Logic using
MATLAB”, Springer, 2007.
4. S.N.Sivanandam · S.N.Deepa, “ Introduction to Genetic Algorithms”, Springer, 2007.
5. Jacek M. Zurada, “Introduction to Artificial Neural Systems”, PWS Publishers, 1992.
MC9296 SOFT COMPUTING LT P C
3 0 0 3
UNIT I INTRODUCTION TO SOFT COMPUTING AND NEURAL NETWORKS 9
Evolution of Computing - Soft Computing Constituents – From Conventional AI to
Computational Intelligence - Machine Learning Basics
UNIT II GENETIC ALGORITHMS 9
Introduction to Genetic Algorithms (GA) – Applications of GA in Machine Learning -
Machine Learning Approach to Knowledge Acquisition.
UNIT III NEURAL NETWORKS 9
Machine Learning Using Neural Network, Adaptive Networks – Feed forward Networks –
Supervised Learning Neural Networks – Radial Basis Function Networks -
Reinforcement Learning – Unsupervised Learning Neural Networks – Adaptive
Resonance architectures – Advances in Neural networks.
UNIT IV FUZZY LOGIC 9
Fuzzy Sets – Operations on Fuzzy Sets – Fuzzy Relations – Membership Functions-
Fuzzy Rules and Fuzzy Reasoning – Fuzzy Inference Systems – Fuzzy Expert Systems
– Fuzzy Decision Making.
UNIT V NEURO-FUZZY MODELING 9
Adaptive Neuro-Fuzzy Inference Systems – Coactive Neuro-Fuzzy Modeling –
Classification and Regression Trees – Data Clustering Algorithms – Rulebase Structure
Identification – Neuro-Fuzzy Control – Case studies.
TOTAL : 45 PERIODS
44
TEXT BOOKS:
1. Jyh-Shing Roger Jang, Chuen-Tsai Sun, Eiji Mizutani, “Neuro-Fuzzy and Soft
Computing”, Prentice-Hall of India, 2003.
2. George J. Klir and Bo Yuan, “Fuzzy Sets and Fuzzy Logic-Theory and
Applications”,Prentice Hall, 1995.
3. James A. Freeman and David M. Skapura, “Neural Networks Algorithms,
Applications, and Programming Techniques”, Pearson Edn., 2003.
REFERENCES:
1. Mitchell Melanie, “An Introduction to Genetic Algorithm”, Prentice Hall, 1998.
2. David E. Goldberg, “Genetic Algorithms in Search, Optimization and Machine
Learning”, Addison Wesley, 1997.
3. S. N. Sivanandam, S. Sumathi and S. N. Deepa, “Introduction to Fuzzy Logic using
MATLAB”, Springer, 2007.
4. S.N.Sivanandam · S.N.Deepa, “ Introduction to Genetic Algorithms”, Springer, 2007.
5. Jacek M. Zurada, “Introduction to Artificial Neural Systems”, PWS Publishers, 1992.
No comments:
Post a Comment
Any doubt ??? Just throw it Here...