PR2022 FUZZY LOGIC AND ANN SYLLABUS | ANNA UNIVERSITY BE PRODUCTION ENGINEERING 6TH SEMESTER SYLLABUS REGULATION 2008 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY SIXTH SEMESTER B.E PRODUCTION ENGINEERING 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), 2008 REGULATION OF ANNA UNIVERSITY CHENNAI AND STUDENTS ADMITTED IN ANNA UNIVERSITY CHENNAI DURING 2009
PR2022 FUZZY LOGIC AND ANN L T P C
3 0 0 3
UNIT I INTRODUCTION TO FUZZY LOGIC PRINCIPLES 9
Basic concepts of fuzzy set theory – operations of fuzzy sets – properties of fuzzy sets –
Crisp relations – Fuzzy relational equations – operations on fuzzy relations – fuzzy
systems – propositional logic – Inference – Predicate Logic – Inference in predicate logic
– fuzzy logic principles – fuzzy quantifiers – fuzzy inference – fuzzy rule based systems –
fuzzification and defuzzification – types.
UNIT II ADVANCED FUZZY LOGIC APPLICATIONS 9
Fuzzy logic controllers – principles – review of control systems theory – various industrial
applications of FLC adaptive fuzzy systems – fuzzy decision making – Multiobjective
decision making – fuzzy classification – means clustering – fuzzy pattern recognition –
image processing applications – systactic recognition – fuzzy optimization – various
UNIT III INTRODUCTION TO ARTIFICIAL NEURAL NETWORKS 9
Fundamentals of neural networks – model of an artificial neuron – neural network
architectures – Learning methods – Taxonomy of Neural network architectures –
Standard back propagation algorithms – selection of various parameters – variations
Applications of back propagation algorithms.
UNIT IV OTHER ANN ARCHITECTURES 9
Associative memory – exponential BAM – Associative memory for real coded pattern
pairs – Applications adaptive reasonance theory – introduction – ART 1 – ART2 –
Applications – neural networks based on competition – kohenen self organizing maps –
learning vector quantization – counter propagation networks – industrial applications.
UNIT V RECENT ADVANCES 9
Fundamentals of genetic algorithms – genetic modeling – hybrid systems – integration of
fuzzy logic, neural networks and genetic algorithms – non traditional optimization
techniques like ant colony optimization – Particle swarm optimization and artificial
immune systems – applications in design and manufacturing.
TOTAL: 45 PERIODS
TEXT BOOKS:
1. S.Rajasekaran.G.A.Vijayalakshmi Pai “Neural Networks, fuzzy logic and genetic
algorithms”, prentice hall of India private limited, 2003
72
2. Timothy J.Ross, “Fuzzy logic with engineering applications”, McGraw Hill, 1995
3. Zurada J.M. “Introduction to artificial neural systems”, Jaico publishing house, 1994
REFERENCES:
1. Klir.G, Yuan B.B. “Fuzzy sets and fuzzy logic prentice Hall of India private limited,
1997.
2. Laurance Fausett, “Fundamentals of neural networks”, Prentice hall, 1992
3. Gen, M. and R. Cheng “Genetic algorithm and engineering design”, john wiley 1997
PR2022 FUZZY LOGIC AND ANN L T P C
3 0 0 3
UNIT I INTRODUCTION TO FUZZY LOGIC PRINCIPLES 9
Basic concepts of fuzzy set theory – operations of fuzzy sets – properties of fuzzy sets –
Crisp relations – Fuzzy relational equations – operations on fuzzy relations – fuzzy
systems – propositional logic – Inference – Predicate Logic – Inference in predicate logic
– fuzzy logic principles – fuzzy quantifiers – fuzzy inference – fuzzy rule based systems –
fuzzification and defuzzification – types.
UNIT II ADVANCED FUZZY LOGIC APPLICATIONS 9
Fuzzy logic controllers – principles – review of control systems theory – various industrial
applications of FLC adaptive fuzzy systems – fuzzy decision making – Multiobjective
decision making – fuzzy classification – means clustering – fuzzy pattern recognition –
image processing applications – systactic recognition – fuzzy optimization – various
UNIT III INTRODUCTION TO ARTIFICIAL NEURAL NETWORKS 9
Fundamentals of neural networks – model of an artificial neuron – neural network
architectures – Learning methods – Taxonomy of Neural network architectures –
Standard back propagation algorithms – selection of various parameters – variations
Applications of back propagation algorithms.
UNIT IV OTHER ANN ARCHITECTURES 9
Associative memory – exponential BAM – Associative memory for real coded pattern
pairs – Applications adaptive reasonance theory – introduction – ART 1 – ART2 –
Applications – neural networks based on competition – kohenen self organizing maps –
learning vector quantization – counter propagation networks – industrial applications.
UNIT V RECENT ADVANCES 9
Fundamentals of genetic algorithms – genetic modeling – hybrid systems – integration of
fuzzy logic, neural networks and genetic algorithms – non traditional optimization
techniques like ant colony optimization – Particle swarm optimization and artificial
immune systems – applications in design and manufacturing.
TOTAL: 45 PERIODS
TEXT BOOKS:
1. S.Rajasekaran.G.A.Vijayalakshmi Pai “Neural Networks, fuzzy logic and genetic
algorithms”, prentice hall of India private limited, 2003
72
2. Timothy J.Ross, “Fuzzy logic with engineering applications”, McGraw Hill, 1995
3. Zurada J.M. “Introduction to artificial neural systems”, Jaico publishing house, 1994
REFERENCES:
1. Klir.G, Yuan B.B. “Fuzzy sets and fuzzy logic prentice Hall of India private limited,
1997.
2. Laurance Fausett, “Fundamentals of neural networks”, Prentice hall, 1992
3. Gen, M. and R. Cheng “Genetic algorithm and engineering design”, john wiley 1997
No comments:
Post a Comment
Any doubt ??? Just throw it Here...