Abstract- In artificial intelligence, an expert system is a computer system that emulates the dec... more Abstract- In artificial intelligence, an expert system is a computer system that emulates the decision making ability of a human expert. Expert systems are designed to solve complex problems by reasoning about knowledge, like an expert, and not by following the procedure of the developer as is the case in conventional programming. An expert system has a unique structure. It is divided into two parts, one fixed, independent of the expert system: the inference engine, and one variable: the knowledge base. To run an expert system, the engine reasons about the knowledge base like a human. When found it can conclude, or infer, the THEN clause, resulting in the addition of new information to its dataset. In other words, it starts with some facts and applies rules to find all possible conclusions. Therefore, it is also known as
Expert system has abilities to reason about situation to give an expert view. According to the sp... more Expert system has abilities to reason about situation to give an expert view. According to the specified requirement of an application different aspect of reasoning is used. CBR is one type of reasoning method which assists the user to solve similar problems. As CBR follow analogical approach instead of following a deductive path. Different types of model and algorithms have been used by CBR. So, the study is based on which and how the different aspect of model and algorithm used in CBR based expert system to make the CBR based system work more appropriately.
Expert Systems are a computer software application whose strength is lies in knowledge base and k... more Expert Systems are a computer software application whose strength is lies in knowledge base and knowledge is acquired from human experts and other source by knowledge engineers, which has the ability to replicate the thinking and reasoning capacity of human being based on some facts and rules present on it. Expert Systems provide an expert view of a problem in a specific domain area by accepting the input from user. But, the input gathered from human are uncertain and ambiguous in nature. As, fuzzy logic is able to handle the uncertainty and ambiguous data, so it is used in expert systems. This paper provides an overview of fuzzy expert systems that have been developed in diverse area and the techniques of reasoning of fuzzy logic used in expert systems.
The proposed SCS expert system, aims to improve the method of selecting the best branch for stude... more The proposed SCS expert system, aims to improve the method of selecting the best branch for student planning to take admission in engineering. The basic idea of the proposed work is to design an expert system which would test the student capabilities by asking questions of the particular branch and gives the result in the form of percentage based on certainty factor concept. The SCS is implemented as a rule-based expert system with two major components-knowledge base and inference engine. The developed inference engine is built using backward chaining method and having certainty factor for reasoning under uncertainty. CLIPS language is used as a tool for designing the SCS expert system.
Knowledge Representation (KR) is the area of AI concerned with how knowledge can be represented s... more Knowledge Representation (KR) is the area of AI concerned with how knowledge can be represented symbolically and manipulated in an automated way by reasoning programs. KR is a combination of data structure and interpretive procedures that leads to knowledgeable behavior. In this paper, an attempt is made to shed more light on KR, and to look at some techniques for it in the real world, with the view to understand their relevance and to realize their crucial usefulness in the development of effective knowledge based (KB) systems. This paper explains various declarative knowledge representations techniques.
In this paper we will discuss a survey on various work done in different areas using Expert Syste... more In this paper we will discuss a survey on various work done in different areas using Expert System(ES). Different methods and algorithms are used in different areas to solve the problem. An expert system is created to solve problems in a particular narrow domain of expertise. There are two different ways developers look at application areas for ES i.e. first, functional nature of problem and secondly, the application domain. One of the key characteristics of an ES is the explanation facility. With this capability, an ES can explain how it arrives at its conclusion. This survey is aimed at reviewing the recent scientific aspects of various research done on ES using different techniques like Case Based Reasoning(CBR), Rule-Based, Fuzzy Logic etc. Keywords— Expert System, Case Based Reasoning, CLIPS,
Abstract- In artificial intelligence, an expert system is a computer system that emulates the dec... more Abstract- In artificial intelligence, an expert system is a computer system that emulates the decision making ability of a human expert. Expert systems are designed to solve complex problems by reasoning about knowledge, like an expert, and not by following the procedure of the developer as is the case in conventional programming. An expert system has a unique structure. It is divided into two parts, one fixed, independent of the expert system: the inference engine, and one variable: the knowledge base. To run an expert system, the engine reasons about the knowledge base like a human. When found it can conclude, or infer, the THEN clause, resulting in the addition of new information to its dataset. In other words, it starts with some facts and applies rules to find all possible conclusions. Therefore, it is also known as
Expert system has abilities to reason about situation to give an expert view. According to the sp... more Expert system has abilities to reason about situation to give an expert view. According to the specified requirement of an application different aspect of reasoning is used. CBR is one type of reasoning method which assists the user to solve similar problems. As CBR follow analogical approach instead of following a deductive path. Different types of model and algorithms have been used by CBR. So, the study is based on which and how the different aspect of model and algorithm used in CBR based expert system to make the CBR based system work more appropriately.
Expert Systems are a computer software application whose strength is lies in knowledge base and k... more Expert Systems are a computer software application whose strength is lies in knowledge base and knowledge is acquired from human experts and other source by knowledge engineers, which has the ability to replicate the thinking and reasoning capacity of human being based on some facts and rules present on it. Expert Systems provide an expert view of a problem in a specific domain area by accepting the input from user. But, the input gathered from human are uncertain and ambiguous in nature. As, fuzzy logic is able to handle the uncertainty and ambiguous data, so it is used in expert systems. This paper provides an overview of fuzzy expert systems that have been developed in diverse area and the techniques of reasoning of fuzzy logic used in expert systems.
The proposed SCS expert system, aims to improve the method of selecting the best branch for stude... more The proposed SCS expert system, aims to improve the method of selecting the best branch for student planning to take admission in engineering. The basic idea of the proposed work is to design an expert system which would test the student capabilities by asking questions of the particular branch and gives the result in the form of percentage based on certainty factor concept. The SCS is implemented as a rule-based expert system with two major components-knowledge base and inference engine. The developed inference engine is built using backward chaining method and having certainty factor for reasoning under uncertainty. CLIPS language is used as a tool for designing the SCS expert system.
Knowledge Representation (KR) is the area of AI concerned with how knowledge can be represented s... more Knowledge Representation (KR) is the area of AI concerned with how knowledge can be represented symbolically and manipulated in an automated way by reasoning programs. KR is a combination of data structure and interpretive procedures that leads to knowledgeable behavior. In this paper, an attempt is made to shed more light on KR, and to look at some techniques for it in the real world, with the view to understand their relevance and to realize their crucial usefulness in the development of effective knowledge based (KB) systems. This paper explains various declarative knowledge representations techniques.
In this paper we will discuss a survey on various work done in different areas using Expert Syste... more In this paper we will discuss a survey on various work done in different areas using Expert System(ES). Different methods and algorithms are used in different areas to solve the problem. An expert system is created to solve problems in a particular narrow domain of expertise. There are two different ways developers look at application areas for ES i.e. first, functional nature of problem and secondly, the application domain. One of the key characteristics of an ES is the explanation facility. With this capability, an ES can explain how it arrives at its conclusion. This survey is aimed at reviewing the recent scientific aspects of various research done on ES using different techniques like Case Based Reasoning(CBR), Rule-Based, Fuzzy Logic etc. Keywords— Expert System, Case Based Reasoning, CLIPS,
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