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 processing is given in Article 128‚ Nature and Scope of AI Techniques‚ Volume 2. Problem solving is the process of finding a solution
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IMSC 500 TERM PAPER FUZZY LOGIC How can a logic which is "fuzzy" be useful? As humans‚ we often rely on imprecise expressions like "usually"‚ "expensive"‚ or "far". But the comprehension of a computer is limited to a black-white‚ everything-or-nothing‚ or true-false mode of thinking. Within conventional logic‚ terms can be only "true" or "false" i.e. either 0 or 1. Fuzzy logic allows a generalization of conventional logic. It provides for terms between "true" and "false" like "almost true"
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support services of human resource development‚ testing‚ evaluation and research & development. A huge industrial base for manufacturing of the agricultural machines has also been developed. Introduction of technologically advanced equipments through extension and demonstration besides institutional credit has also been taken up. Equipments for resource conservation have also been adopted by the farmers. Under various governments sponsored schemes like Macro Management of Agriculture‚ Technology
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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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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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follow up action of agricultural development‚ strategy to increase agricultural production by raising unit yield and expanding higher cropped area from available irrigable area. DOI has initiated various irrigation schemes. DOI also taking loan assistance from various sources so that irrigation facilities can be increased. The Kurung Khola Non-convention I.P. is one of the projects requested by the user farmers. It lies in Thumpokhara ward no.3 of Syangja district. The proposed command area of
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METHODS OF IRRIGATION The manner in which water is applied to the land is commonly referred to as method of irrigation. These methods are adopted to apply irrigation water to the crop depending on the landscape‚ amount of water and equipment available‚ the crop and method of cultivation of crop. The main aim of these methods is to store water in the effective root zone uniformly and in maximum quantity ensuring minimum water loss and to get optimum yield. Various methods of irrigation are: 1. Surface
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C HAPTER S EVENTEEN FUZZY LOGIC Slumber not in the tents of your fathers. The world is advancing. Advance with it. —Giuseppe Mazzini Industrial Text & Video Company 1-800-752-8398 www.industrialtext.com SECTION 5 Advanced PLC Topics and Networks Fuzzy Logic CHAPTER 17 C HAPTER H IGHLIGHTS Fuzzy logic provides PLCs with the ability to make “reasoned” decisions about a process. In this chapter‚ we will introduce you to the basics of fuzzy logic‚ including fundamental concepts
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Fuzzy Logic based Controller to improve Demand Side Management Nivedita Patnaik Department of Electrical Engineering Indian Institute of Technology‚ Kharagpur – 721302‚ India Abstract Energy demand management or Demand Side Management (DSM) involves actions that influence the pattern of energy consumption by consumers. In this paper a fuzzy logic based approach towards shifting the average power demand of residential electric water heaters has been discussed. Power system demand side management
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EMBEDDED LEARNING ROBOT WITH FUZZY Q-LEARNING FOR OBSTACLE AVOIDANCE BEHAVIOR Khairul Anam1‚Prihastono2‚4‚Handy Wicaksono3‚4‚ Rusdhianto Effendi4‚ Indra Adji S5‚ Son Kuswadi5‚ Achmad Jazidie4‚ Mitsuji Sampei6 1 Department of Electrical Engineering‚ University of Jember‚ Jember‚ Indonesia (Tel : +62-0331-484977 ; E-mail: kh.anam.sk@gmail.com) 2 Department of Electrical Engineering‚ University of Bhayangkara‚ Surabaya‚ Indonesia (Tel : + 62-031-8285602; E-mail: prihtn@yahoo.com) 3 Department
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