expert system


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expert system,

a computer system or program that uses artificial intelligenceartificial intelligence
(AI), the use of computers to model the behavioral aspects of human reasoning and learning. Research in AI is concentrated in some half-dozen areas.
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 techniques to solve problems that ordinarily require a knowledgeable human. The method used to construct such systems, knowledge engineering, extracts a set of rules and data from an expert or experts through extensive questioning. This material is then organized in a format suitable for representation in a computer and a set of tools for inquiry, manipulation, and response is applied. While such systems do not often replace the human experts, they can serve as useful adjuncts or assistants. Expert systems have been applied to chemistry, geology, genetic engineering, medicine, and pharmacology.

expert system

[′ek‚spərt ‚sis·təm]
(computer science)
A computer system composed of algorithms that perform a specialized, usually difficult professional task at the level of (or sometimes beyond the level of) a human expert.

expert system

(artificial intelligence)
A computer program that contains a knowledge base and a set of algorithms or rules that infer new facts from knowledge and from incoming data.

An expert system is an artificial intelligence application that uses a knowledge base of human expertise to aid in solving problems. The degree of problem solving is based on the quality of the data and rules obtained from the human expert. Expert systems are designed to perform at a human expert level. In practice, they will perform both well below and well above that of an individual expert.

The expert system derives its answers by running the knowledge base through an inference engine, a software program that interacts with the user and processes the results from the rules and data in the knowledge base.

Expert systems are used in applications such as medical diagnosis, equipment repair, investment analysis, financial, estate and insurance planning, route scheduling for delivery vehicles, contract bidding, counseling for self-service customers, production control and training.

expert system

An artificial intelligence (AI) application that uses a knowledge base of human expertise for problem solving. Its success is based on the quality of the data and rules obtained from the human expert. In practice, expert systems perform both below and above that of a human.

The expert system derives its answers by running the knowledge base through an inference engine, which is software that interacts with the user and processes the results from the rules and data in the knowledge base.

Examples are medical diagnosis, equipment repair, investment analysis, financial, estate and insurance planning, vehicle routing, contract bidding, production control and training. See chatbot, virtual assistant, AI and EPSS.


Expert System
References in periodicals archive ?
These modules represent the analysis process of expert system and its components are described below:
In the process of system operation, this knowledge and experience can be continuously increased and modified; the expert system to solve the problem is the real life of only the field experts to solve the problem.
Table 1 shows the comparison of fuzzy, intutuionistic fuzzy, and neutrosophic expert system and their ability to represent different uncertainty data types.
The expert that understands the necessity of using an expert system in his activity domain can obtain help from the knowledge engineer (IT specialist) because following discussions with him, som knowledge will be reformulated in a way that it can be applied on a computer.
To design an expert system, regardless of the application and its context, steps must be completed.
For developing the expert system, Microsoft Visual Basic.NET was used.
The research questions were as follows: what information is currently available on diagnostic expert systems in rheumatology, how do these systems work, what is their validity and their applicability in daily practice, and finally what is an optimal diagnostic expert system expected to be.
In the domain of pavement management, Kaur and Tekkedil (2000) developed a fuzzy expert system, which employs the information about the materials used, thickness of the flexible pavement layers, traffic characteristics, and road age to predict the pavement performance in the form of rut depth.
Stanford University professor emeritus Edward Feigenbaum, known as "the father of expert systems," was named the IEEE Computer Society's 2013 Computer Pioneer Award recipient.
Researchers have explored every aspect of fuzzy philosophy and the studies reported on fuzzy expert systems in medical diagnosis covers wide spread area including the need, importance, potential and approaches for designing the expert systems for medical diagnosis.[3,4,10,13] Computer assisted applications for patient's diagnosis and treatment seems to be the more recent area of interest.[2,5,18,20,21] The Fuzzy Expert System has proved its usefulness significantly in the medical diagnosis for the quantitative analysis and qualitative evaluation of medical data, consequently achieving the correctness of results.
An expert system based on the statute will ask you questions about your specific situation and then provide answers concerning whether and how the law applies to you.

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