Abraham Oklahoma State University‚ Stillwater‚ OK‚ USA 1 Problem Solving Using Heuristics 2 What are Rule-based Systems? 3 Inference Engine in Rule-based Systems 4 Expert System Development 5 Fuzzy Expert Systems 6 Modeling Fuzzy Expert Systems 7 Illustration of Fuzzy Expert System Design 8 Adaptation of Fuzzy Inference Systems 9 Summary References 909 910 911 911 912 914 914 918 918 919 1 PROBLEM SOLVING USING HEURISTICS A general introduction to artificial intelligence methods of measurement signal
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Diagnostics Based on Fuzzy Neural Networks* DONG Mingchui (董名垂)**‚ CHEANG Takson (郑德信)†‚ CHAN Sileong (陈思亮)† Department of Automation‚ Tsinghua University‚ Beijing 100084‚ China; † Faculty of Science and Technology‚ University of Macau‚ Macau‚ China Abstract: An on-line method was developed to improve diagnostic accuracy and speed for analyzing running motors on site. On-line pre-measured data was used as the basis for constructing the membership functions used in a fuzzy neural network (FNN) as
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[pic] A HIGH PERFORMANCE INDUCTION MOTOR DRIVE SYSTEM USING FUZZY LOGIC CONTROLLER [pic] VIGNAN’S ENGINEERING COLLEGE VADLAMUDI A HIGH PERFORMANCE INDUCTION MOTOR DRIVE SYSTEM USING FUZZY LOGIC CONTROLLER ABSTRACT Abstract- Basically‚ the motor drive system comprises a voltage source inverter-fed induction motor (VSIM): namely a three-phase voltage source inverter and the induction motor. The squirrel-cage induction motor voltage equations are based on an orthogonal
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CHAPTER I 1. Fuzzy control Fuzzy control is a practical alternative for a variety of challenging control applicationssince it provides a convenient method for constructing nonlinear controllersvia the use of heuristic information. In a sense fuzzy systems can be “trained” and can “learn” how to perform throughout a control task and are considered as intelligent control system. Fuzzy control system design is based on empirical methods‚ basically a methodical approach to trail-and-error. The
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Journal of Intelligent & Fuzzy Systems 21 (2010) 365–378 DOI:10.3233/IFS-2010-0457 IOS Press 365 A theorical model design for ERP software selection process under the constraints of cost and quality: A fuzzy approach Semih Onut∗ and Tugba Efendigil Department of Industrial Engineering‚ Yildiz Technical University‚ Yildiz‚ Istanbul‚ Turkey Abstract. Enterprise Resource Planning (ERP) software selection is one of the most important decision making issues covering both qualitative and quantitative
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Background Significance of Research 5 6 2.0 Introduction 6 2.1 Traffic Light Controller 6 2.2 Fuzzy Set 8 2.3 Membership Function 10 2.3.1 Mathematical Concept for Fuzzy Logic 13 2.3.2 Basic Operations 3 LITERATURE REVIEW 16 17 3.0 Introduction 17 3.1 Fuzzifier 17 3.2 Fuzzy Inferences System 18 3.2.1 Fuzzy IF-THEN rules 19 3.2.2 Mamdani ’s Method 21 ANALYSIS AND DISCUSSION 24 4.1 Calculation for Mamdani-Type
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TERMPAPER OF APPLICATION OF FUZZY AUTOMATA THEORY Formal Languages and Automation Theory (CAP632) ?Submitted To: - ?Submitted By: - Miss. Kiran Sharma Name: -Dheeraj Sharma Section: -D1207 Roll No:-RD1207A09 Regd No: -11207869
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Precise Fuzzy Inference Systems I. INTRODUCTION Fuzzy inference is the process of mapping an input to an output using fuzzy logic. It consists of membership functions which are responsible for the fuzzification of inputs‚ fuzzy operators and IF-THEN rules. Fuzzy inference systems have been successfully applied in many different fields‚ such as automatic control‚ data classification‚ decision analysis‚ expert systems‚ and computer vision. And because of this multidisciplinary characteristic
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Fuzzy Analytical Hierarchy Process (FAHP) Based Model for Multi Criteria Decision Making (MCDM) Parag A. Guruji‚ Chandan M. Bhattad Department of Computer Science and Engineering‚ Walchand College of Engineering Sangli (An Autonomous Institute) Vishrambag‚ Sangli‚ Maharashtra‚ India- 416415 gurujipa@gmail.com chandan.bhattad@rediffmail.com Abstract: The application of fuzzy AHP to the multi criteria decision making has brought great improvement in the realistic decision making by providing
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1007/s00170-005-2562-8 ORIGINAL ARTICLE A. Noorul Haq · G. Kannan Fuzzy analytical hierarchy process for evaluating and selecting a vendor in a supply chain model Received: 23 October 2004 / Accepted: 12 January 2005 / Published online: 16 November 2005 © Springer-Verlag London Limited 2005 Abstract The paper proposes a structured model for evaluating vendor selection using the analytical hierarchy process (AHP) and fuzzy AHP. The model is developed using evidence from an empirical study. The
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