SCHOOL OF COMPUTER SCIENCE AND ENGINEERING ... Limin Fu , “Neural
Network in computer intelligence”, McGraw-Hill International. Editions,1994. 2.
Course Code Course Title Semester Course Time
: : : :
SRM UNIVERSITY FACULTY OF ENGINEERING AND TECHNOLOGY SCHOOL OF COMPUTER SCIENCE AND ENGINEERING DEPARTMENT OF CSE COURSE PLAN CS0695 Intelligent systems M.Tech ,III Sem (Elective) July-Dec 2013
Day
Hour 2 4 5 1
Day 1 Day 1 Day 2 Day 3 Location Faculty Details Name
Timing 09.35am-10.25am 11.25am- 12.15pm 01.30pm-02.20pm 08.45am-09.35am
: University Building (Room No. 805)
Dr.S.Prabakaran
Office Tech Park (Room No. 706 A)
Office hour Monday to Friday
Mail id
[email protected]
Required Text Books: 1. Limin Fu , “Neural Network in computer intelligence”, McGraw-Hill International Editions,1994. 2. Timoothy J. Ross , “Fuzzy Logic with Engineering Applications”, McGraw-Hill International Editions,1997
Reference Books 3. Nils J.Nilsson ,“Principles of Artificial Intelligence”, Narosa Publishing, 1980 4. Elaine Rich and Kelvin knight, “Artificial Intelligence”, McGraw-Hill Edition.1991 5. David E. Goldberg , “Genetic Algorithms-In Search, optimization and Machine Learning”, Pearson Education. 6. George.J.Klin / Bo Yuan , “Fuzzy Systems & Fuzzy Logic – Theory and Applications” , Prentice, Hall of India,1995.
Web resources 1. www.pafkiet.edu.pk/coe/Artificial_Intelligence.ppt aci2.ncat.edu/gvdozier/ACI_LectureNotes/Introduction.ppt 1
2. www.intelligence.org/ 3. www.cse.hcmut.edu.vn/.../ai/AI,%20APOC%20-%20Chapter%2009,%20KBR.pdf 4. www.freebookcentre.net/.../Free-Artificial-Intelligence-Books-Download.html 5. http://books.google.co.in/books/about/Neural_Computing_An_Introduction.html?id=pVR9W5L EZUwC&redir_esc=y 6. www.sciencedirect.com/science/book/9780340705896 7. http://www.springer.com/computer/ai/book/978-3-642-18859-6 8. www.pes.edu/mcnc/AI/data/presentation/Turban&Aronson/ch16.ppt 9. www.neiu.edu/~mosztain/cs335/lecture05.ppt 10. freepdfdb.org/pdf/fuzzy-system-ppt 11. www.powershow.com 12. http://books.google.co.in/books?id=x9SMzhmEhf0C&pg=PA255&dq=%22fuzzy+system%22+ PPT&hl=en&sa=X&ei=nfbwUZmwFoWErAfv84D4AQ&ved=0CCMQ6AEwAA#v=onepage& q=%22fuzzy%20system%22%20PPT&f=false 13. www2.cs.siu.edu/~rahimi/cs437/slides/lec11-short.ppt 14. www.computing.surrey.ac.uk/.../week10_Hybrid_Intelligent_Systems.ppt 15. www.cse.unr.edu/~looney/cs773b/FNNtutorial.pdf Detailed Session Plan PURPOSE This course provides a way to understand the concepts of Artificial Intelligence , ANN , Genetic Algorithms and Fuzzy systems and its applications
INSTRUCTIONAL OBJECTIVES •To understand the Basics of AI and ANN • To learn about Neuro fuzzy systems and to study their applications • To learn Genetics algorithms and to understand its applications
Cycle Test Model Exam Term paper/seminar Surprise Test Attendance
: : : : :
25 Marks 25 Marks 10Marks 5 Marks 5 Marks
Test Schedule S.No. 1
DATE
TEST Cycle TestI
TOPICS Unit I & II
DURATION 2 periods 2
2
Model exam
All units
Course outcome
3 Hrs
Program outcome To be familiar with the basics of AI and ANN
To understand the Basics of AI and ANN To learn about Neuro fuzzy systems and to study their applications
To analyse and appreciate the practical applications of the neuro fuzzy system
To learn Genetics algorithms and to understand its applications
To get an idea of various types of genetic algorithms and its applications and to apply them in solving practical problems
UNIT I
9
ARTIFICIAL INTELLIGENCE
Some Applications of AI-Production Systems and AI-Different types of Production Systems-Search Strategies for AI-Backtracking-Graph-search, Ununiformed and Heuristic Graph-Search Procedures-Related AlgorithmsApplications.
S.No
Topic to be corrected
Time (min)
Ref
Teaching method
Testing Method
1
Introduction to AI
50
3,4
BB
2
Some Applications of AI
50
3,4
BB, PPT
Illustration by examples
3 4 5 6 7
Production Systems and AI Different types of Production Systems Search Strategies for AI-Backtracking Ununiformed Graph-search Heuristic Graph-Search Procedures
50 50 50 50 50
3,4 3,4 3,4 3,4 3,4
BB,PPT PPT BB PPT PPT
Discussion Quiz Quiz Assignment surprise test
8
Related Algorithms-Applications.
50
3,4
PPT
Quiz
9
Recapitulation
50
3,4
PPT
test
UNIT I I
Discussion
9
INTRODUCTION TO NEURAL COMPUTING
Differences between Human Brain and ANN - Knowledge Based Information Processing-Neural Information Processing - Hybrid Intelligence - Basic Concepts of Neural Networks - Inference and Learning - Classification, Association, Optimization and Self-Organization Models-Learning-Supervised And Unsupervised.
10 11 12
Introduction to Neural computing Differences between Human Brain and ANN Knowledge Based Information Processing
50
1
BB
Discussion
50
1
BB
Discussion
50
1
PPT
Quiz 3
16
Neural Information Processing - Hybrid Intelligence Basic Concepts of Neural Networks Inference and Learning Classification, Association, Optimization and Self-Organization Models
17 18
Learning-Supervised And Unsupervised Recapitulation
13 14 15
50
1
BB
Quiz
50 50
1 1
BB BB
Quiz Assignment
50
1
PPT
Discussion
50 50
1 1
PPT PPT
Discussion Discussion
UNIT-III FUZZY SYSTEMS 9 Crisp sets and Fuzzy sets-Notion of Fuzzy Sets - Basic Concepts - Operations on Fuzzy sets-Uncertainty and Information – Types of Uncertainty –Principles of Uncertainty and Information –Applications
19
Introduction to fuzzy systems
50
1
PPT
Group discussion
20
Crisp sets and Fuzzy sets
50
1
PPT
Group discussion
21
Notion of Fuzzy Sets
50
1
PPT
22
Basic Concepts of fuzzy sets and operations
50
1
PPT
23
Uncertainty and Information
50
1
BB
24
Types of Uncertainty
50
1
BB
Group discussion,
25
Principles of Uncertainty and Information
50
1
BB
Group discussion
26
Applications
50
1
PPT
27
Recapitulation
50
1
BB
Brain storming Assignment Group discussion
Group discussion Assignment Group discussion Assignment Group discussion, Surprise test
UNIT-IV NEURO FUZZY SYSTEM 9 Introduction to Neuro - Fuzzy Systems -Fuzzy System Design Procedures – Fuzzy Sets and Logic Background Fuzzy / ANN Design and Implementation
28
Introduction to neuro fuuzzy system
50
1
PPT
Quiz
29
Fuzzy System Design Procedures
50
1
PPT
Group discussion Quiz
30
Fuzzy System Design Procedures
50
1
PPT
Group discussion
31
Fuzzy Sets
50
1
PPT
Group discussion
32
Logic Background of fuzzy sets
50
1
BB
Discussion
33
Fuzzy / ANN Design and Implementation
50
1
PPT
Group discussion
34
Fuzzy / ANN Design and Implementation
50
1
PPT
Group discussion
35
Fuzzy / ANN Design and Implementation
50
1
PPT
Brain storming
36
Recapitulations
50
1
BB
Quiz, Assignment, Group discussion 4
UNIT –V
GENETIC ALGORITHMS
Introduction-Robustness of Traditional, Optimization and Search Techniques-The goals of optimizationComputer Implementation-Applications
37 38 39 40 41 42 43 44 45
Introduction to Genetic algorithms Traditional,Optimization and Search Techniques Robustness of Traditional Optimization and Search Techniques The goals of optimization Computer Implementation Applications Applications Web resources for genetic algorithm Recapitulations
BB – Black Board
50
1
PPT
Group discussion
50
1
PPT
Group discussion
50
1
BB
Group discussion
50 50 50 50 50
1 1 1 1 1
BB PPT BB BB PPT
50
1
BB
Group discussion Group discussion Discussion Assignment Group discussion Group discussion, Assignment
PPT – Power Point Presentation
Prepared By
Approved By
Dr PRABAKARAN
HOD/CSE
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