Application of Expert Systems and Simulation Modeling to Calculate Connectivity Between the Nodes of the Graph
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Expert system is made to transfer the expert knowledge into the system, so it hopefully can give solution to problem.“Expert system for diagnosis of infection TBC lung disease” is an alternative for the various expert system that can be used to overcome the problem. The aim of designing expert system is for diagnosis of infection TBC lung disease, should that users can diagnose towards this illnes based on symptoms put into this system. Development of expert system uses knowledge base stored in database using Paradox, rule based with forward chaining method.The result of consultation with the system indicate that this system can determine disease and suggestion based on symptoms inputed by user. Keyword : Expert System, Forward Chaining, Knowledge Base
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Of late, expert system is the biggest single use technique amongst the artificial intelligence techniques. An expert system is an artificial intelligent programme incorporating a knowledge base, an inference engine and the user interface. Whether it is in medicine, Mineral exploration, evaluation of chemical structure or in industrial applications, expert system has established its wider role and applicability as far as expert decisions are concerned. The biggest flexibility of an expert system is that, it permits a non-expert to do the work of an expert. The aim of this paper is to consolidate the various steps and methodologies for the development, operation and application of expert system for problem solving and in industrial applications.
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Using object oriented method, the design and implementation of the Agricultural Expert System Tool were developed. With this tool, agricultural experts can develop their own expert systems without the help of knowledge engineer. Many expert systems were developed with this tool, such as cucumber diseases expert system, apple diseases expert system, apple pests expert system, apple tree fertilization expert system and cotton diseases expert system.
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The paper describes the different classifications of expert systems. There are mainly five types of expert systems. They are rule based expert system, frame based expert system, fuzzy expert system, neural expert system and neuro-fuzzy expert system. We discussed the expert systems based on their knowledge representation, inference engine, working of the system and user interface. At the end, we provided comparative study of above five types of expert systems based on different parameters. We can say that choice of an expert system depends on the domain requirements.
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Concrete pump technology depends on experts in the special field to resolve complexity and faintness at all times in expert system.Network expert system is a great development at artificial intelligence and expert system.It conquers many difficulties in obtaining and expressing knowledge.Owing to simulating cerebra's thinking,its reasoning power is better than tradition's.Expert system based on neural network only need examples that is about the expert field to train the neural network.This expert system can get same output alike the genuine expert if there are same inputs.The precision of the expert system's outputs is resemble as the real field expert.This article is about network expert system's obtaining and expressing knowledge and reasoning power.
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AbstractThe paper gives an overview of expert systems discussing all aspects concerned with them. Starting with the definition and evolution of expert systems the paper tells how, from the traditional mainstream of Artificial intelligence the growth of expert systems took place. Then the architecture and working of expert system is analyzed, giving details about the working of each component and its functions. Expert system shells and blackboards which have become an integral part of expert systems are also analyzed. Inference mechanisms used in expert systems and the design considerations while creating an expert system are also considered. Lastly the paper concludes with a case study of MYCIN (a famous expert system) and the challenges before the current expert systems to reach the next generation of expert systems. Additional informationNotes on contributorsAniruddha DuttaAniruddha Dutta obtained his bachelor of Engineering degree in Computer Science and Engineering from Manipal Institute of Technology, Manipal India in 2005. He is currently working in Infosys Technologies Ltd., in Bangalore. He is pursuing software development in the company and also is in touch with Professor A Bhattacharyya of DCE, for investigating in some research problems in the area of computer engineering.Asok BhattacharyyaAsok Bhattacharyya has obtained his Ph.D in Radiophysics and Electronics in 1981 and is working in Delhi College of Engineering w.e.f. 1974 in various capacities. He is at present Professor and Head of Electronics and Communication Engineering Department in Delhi College of Engineering and is a Professor of Electronics and Communication in the Faculty of Technology, Delhi University. His teaching interest is in the area of Analog and Digital Electronics, Computer Architecture & Microprocessors, VLSI and Fault-Tolerant Computing. His research interest is in the area of easily testable and diagnosing digital systems, advance analog circuit design, VLSI design and embedded system, medical image processing, pervasive computing, etc. He wrote a research monograph “checking experiments in sequential machines” with M/s John Wiley & Sons Inc. He is a fellow of IETE, Life member of ISTE and a senior member of IEEE.
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Wang, Y. B. and Mack, T. P., Expert systems in agriculture.An expert system is a computer program that simulates the reasoning of a human expert. This paper discusses the definition, elements, and common characteristics of expert systems. It details the steps used in building a small expert system and the implementation of an expert system.Expert systems mimic human capabilities in solving a wide variety of problems in agriculture. There are many agricultural applications for expcrt systems programming, such as agricultural planning, diagnostics, and management, etc. Some expert systems are detailed. COMAX is the first successful example for using expert systems technology in agricultural integrated crop management. Pest management is an important field for expert systems. A small expert system in forestry pest management named PREDICT and expert systems techniques for to insect pest alfalfa management are also described. In addition, an expert system applied to grain marketing analysis is detailed.
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Expert elicitation
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