Intelligent SystemIntelligent SystemMing-Feng Yeh Ming-Feng Yeh

Department of Electrical EngineeringLunghwa University of Science and Technology

E-mail: mfyeh@mail.lhu.edu.twWebsite: http://mfyeh.myweb.hinet.net

Office: F412B-III Tel: #5518

Ming-Feng Yeh 2

IntroductionIntroductionWhat is an “intelligent system”?It is hard to define what exactly an “intelligent system” is.No one can deny that the intelligent system already has an increasing impact on the quality of life in many areas.Intelligence in a system refers to its ability to learn or adapt, and to modify its functional dependences in response to new experiences or due to changes in the functional relationship.

Ming-Feng Yeh 3

IntroductionIntroduction

This course will focus on introducing the intelligent system technologies.The students are expected to learn the basic modeling techniques and to know where to apply the knowledge.

The following materials will be covered in this course:

Ming-Feng Yeh 4

CONTENTSCONTENTSGrey System Theory Grey Model / Grey Prediction Grey Relational Analysis

Fuzzy Control Fuzzy Logic Fuzzy Control

Neural Networks Neural Networks Cerebellar Model Articulation Controller Genetic Algorithm

Hybrid SystemsApplications

Ming-Feng Yeh 5

SYLLABUSSYLLABUS

TextbookTextbook: No textbook. Some references will be assigned in the

class.

Evaluation Criteria:Evaluation Criteria: Midterm Oral Report: 50% Final Oral Report: 50%

Ming-Feng Yeh 6

Soft Soft / / Hard ComputingHard Computing

Hard computing whose prime desiderata are precision, certainty, and rigor.Soft computing is tolerant of imprecision, uncertainty, and partial truth. (Lotfi Zadeh)

The primary aim of soft computing is to exploit such tolerance to achieve tractability, robustness, a high level of machine intelligence, and a low cost in practical applications.Fuzzy logic, neural networks (including CMAC), probabilistic reasoning (genetic algorithm, evolutionary programming, and chaotic systems)

Ming-Feng Yeh 7

Soft ComputingSoft Computing

Methodology Strength

Neural network Learning and adaptation

Fuzzy set theory Knowledge representation via fuzzy if-then rule

Genetic algorithm and simulated annealing

Systematic random search

Conventional AI Symbolic manipulation

Ming-Feng Yeh 8

Computational IntelligenceComputational Intelligence

Fuzzy logic, neural network, genetic algorithm, and evolutionary programming are also considered the building blocks of computational intelligence. (James Bezdek)

Computational intelligence is low-level cognition in the style of human brain and is contrast to conventional (symbolic) artificial intelligence (AI).