TECHNOLOGIES OF EXPERT SYSTEMSCONSTRUCTION FOR ELECTRIC POWER

AbstractIn the past decade, expert systems have been applied to a wide variety of application tasks. A central problem of expert system development and maintenance is the demand placed on knowledge engineers and domain experts. A commonly proposed solution is knowledge-acquisition tools. This paper reviews a class of knowledge-acquisition tools that presuppose the problem-solving method, as well as the structure of the knowledge base. These explicit problem-solving models are exploited by the tools during knowledge-acquisition, knowledge generalization, error checking and code generation.

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Diagnose Expert System Computer Malfunction Certainty Factor Method

Journal Of Computer Networks, Architecture and High Performance Computing ◽

10.47709/cnapc.v2i1.358 ◽

2020 ◽

Vol 2 (1) ◽

pp. 63-71

Author(s):

Djouking Kiray ◽

Fricles Ariwisanto Sianturi

Keyword(s):

Decision Making ◽

Expert System ◽

Expert Systems ◽

Knowledge Base ◽

Base System ◽

Certainty Factor ◽

Factor Method ◽

Knowledge Base System ◽

Two Factors ◽

Computer Based

An expert system is a knowledge base system that solves problems using an expert's knowledge that is entered into a computer, thereby increasing productivity, Because an expert can work faster than a human lay works like an expert. Expert systems Also solve problems by imitating the ways in the which an expert expert offer section with problems in his field, one of the which is in the field of computer repair, the problem of computer damage Becomes a fairly complicated problem, this problem is Generally experienced by individuals and institutions. One of them is in school institutions that have computer laboratories. to diagnose computer use can damage the certainty factor method that helps identify damage to the computer and find the cause of damage to the computer based on the symptoms that occur and the solution to repair it. Certainty Factor is one of the techniques used to deal with uncertainty in decision making. In dealing with a problem, answers are Often found that do not have full certainty. This uncertainty is influenced by two factors items, namely the uncertain rules and user uncertain answers. Uncertain rules are rules of symptoms that are determined for a damage.

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The application of expert systems in the clinical laboratory.

Clinical Chemistry ◽

10.1093/clinchem/35.8.1595 ◽

1989 ◽

Vol 35 (8) ◽

pp. 1595-1600 ◽

Cited By ~ 28

Author(s):

P Winkel

Keyword(s):

Expert System ◽

Expert Systems ◽

Knowledge Base ◽

Clinical Laboratory ◽

Laboratory Medicine ◽

General Nature ◽

Inference System

Abstract An "expert system" consists of a knowledge base containing information of a general nature and an inference system that receives data from the user and applies the knowledge base to produce advice and explanations. An expert system stripped of its knowledge base (a tool) may be used to build new expert systems. Existing systems relevant for laboratory medicine are reviewed. The role in the laboratory of expert systems and their integration and evaluation are discussed.

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Method for Attack Tree Data Transformation and Import Into IT Risk Analysis Expert Systems

Applied Sciences ◽

10.3390/app10238423 ◽

2020 ◽

Vol 10 (23) ◽

pp. 8423

Author(s):

Donatas Vitkus ◽

Jonathan Salter ◽

Nikolaj Goranin ◽

Dainius Čeponis

Keyword(s):

Expert System ◽

Risk Analysis ◽

Expert Systems ◽

Knowledge Base ◽

Automated Analysis ◽

Knowledge Bases ◽

It Security ◽

Security Risk ◽

Attack Tree ◽

Attack Trees

Information technology (IT) security risk analysis preventatively helps organizations in identifying their vulnerable systems or internal controls. Some researchers propose expert systems (ES) as the solution for risk analysis automation since risk analysis by human experts is expensive and timely. By design, ES need a knowledge base, which must be up to date and of high quality. Manual creation of databases is also expensive and cannot ensure stable information renewal. These facts make the knowledge base automation process very important. This paper proposes a novel method of converting attack trees to a format usable by expert systems for utilizing the existing attack tree repositories in facilitating information and IT security risk analysis. The method performs attack tree translation into the Java Expert System Shell (JESS) format, by consistently applying ATTop, a software bridging tool that enables automated analysis of attack trees using a model-driven engineering approach, translating attack trees into the eXtensible Markup Language (XML) format, and using the newly developed ATES (attack trees to expert system) program, performing further XML conversion into JESS compatible format. The detailed method description, along with samples of attack tree conversion and results of conversion experiments on a significant number of attack trees, are presented and discussed. The results demonstrate the high method reliability rate and viability of attack trees as a source for the knowledge bases of expert systems used in the IT security risk analysis process.

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Pest Plant Disease Prevention and Identification System Using Certainty Factor Method

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i3.2.18750 ◽

2018 ◽

Vol 7 (3.2) ◽

pp. 763 ◽

Cited By ~ 1

Author(s):

Robbi Rahim ◽

Nuning Nurna Dewi S ◽

M Zamroni ◽

Lilla Puji Lestari ◽

Muh Barid Nizarudin Wajdi ◽

...

Keyword(s):

Expert System ◽

Disease Prevention ◽

Expert Systems ◽

Knowledge Base ◽

Plant Disease ◽

Expert Knowledge ◽

Identification System ◽

Certainty Factor ◽

Factor Method

Diseases in plants are something that can happen to many plants either caused by pests or other factors, the disease in plants can be detected based on the symptoms that appear on the plant before spreading to all plants, to recognize the symptoms and types of diseases contained in plants require plant experts or also by applying expert systems with expert knowledge base applied to the system by using certain methods such as certainty factor method. Expected results with the availability of this expert system to the user can help many users to detect diseases in plants.

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Utilisation des systèmes experts en psychiatrie

The Canadian Journal of Psychiatry ◽

10.1177/070674379303800309 ◽

1993 ◽

Vol 38 (3) ◽

pp. 203-211 ◽

Cited By ~ 5

Author(s):

Maurice M. Ohayon

Keyword(s):

Expert System ◽

Expert Systems ◽

Knowledge Base ◽

Clinical Studies ◽

Real Life ◽

Logical Structure ◽

Production Rules ◽

Agreement Rate ◽

Clinical Criteria ◽

Major Benefit

Are expert systems liable to be used as consultants in psychiatry? Most expert systems deal with an over-restricted part of psychiatry and cannot be a real help in everyday care. Moreover, most of them are not actually validated (the comparison between the system's and the expert's conclusions in a few cases is not enough). Another problem is that they reflect the uncertainties of nosographie problems. Validation of such systems needs the careful checking of the logical structure of the underlying nosography, the fitness of the structure's knowledge base and the fitness of the inference engine. Moreover, the naïve use of the system by untrained clinicians is the best means of validation since it provides real life proof of the ability of expert systems to make diagnoses in unselected cases where the need for a common diagnostic reference is clear (for example, epidemiologic, psychopharmacological ornosographic research). Some of the best known expert systems in the field of psychiatry are reviewed and another expert system, Adinfer, is presented. Developed since 1982, Adinfer is a forward-tracking level O system (in its simplified version for micro-computers). The knowledge base is a translation of the DSM-III-R into production rules. The program has been included in several softwares packages and used in many clinical studies, both among psychiatrists and physicians. The program has been validated with 1,141 unselected cases, and with 47 physicians: an 83% agreement rate was found between the system's and the physician's diagnoses, taking into account that the clinicians were asked to give their conclusions according to their usual nosography. Many of the 16% discrepancies were accounted for by the differences in the nosographie classes, since they were found mainly in the “atypical psychotic” and “organic” disorders. A major benefit of expert systems is that they provide a common “expert” in multicentric studies and prevent loose checking of clinical criteria.

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Knowledge Acquisition for Large-Scale Expert Systems in Transportation

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1651-09 ◽

1998 ◽

Vol 1651 (1) ◽

pp. 59-65

Author(s):

Jeffrey L. Adler ◽

Eknauth Persaud

Keyword(s):

Expert System ◽

Expert Systems ◽

Knowledge Acquisition ◽

Knowledge Base ◽

Traditional Knowledge ◽

Large Scale ◽

Knowledge Engineering ◽

Problem Domain ◽

Client Server ◽

Server Application

One of the greatest challenges in building an expert system is obtaining, representing, and programming the knowledge base. As the size and scope of the problem domain increases, knowledge acquisition and knowledge engineering become more challenging. Methods for knowledge acquisition and engineering for large-scale projects are investigated in this paper. The objective is to provide new insights as to how knowledge engineers play a role in defining the scope and purpose of expert systems and how traditional knowledge acquisition and engineering methods might be recast in cases where the expert system is a component within a larger scale client-server application targeting multiple users.

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A Desktop Expert System as a Human Factors Work Aid

Proceedings of the Human Factors Society Annual Meeting ◽

10.1177/154193128703101002 ◽

1987 ◽

Vol 31 (10) ◽

pp. 1087-1090 ◽

Cited By ~ 1

Author(s):

Craig S. Hartley ◽

John R. Rice

Keyword(s):

Expert System ◽

Human Factors ◽

Expert Systems ◽

Knowledge Base ◽

System Development ◽

Scientific Publication ◽

Problem Area ◽

Video Display ◽

Problem Domain ◽

Topic Area

The advent of increasingly powerful microcomputers, coupled with the development of small, feature-packed expert systems now makes it cost effective to provide workers with relatively inexpensive desktop expert systems. In order to evaluate the value of such systems as work aids for human factors engineers, we developed a small demonstration system using a commercially available expert system development tool, NEXPERTTM, released in 1985 by Neuron Data, Inc. of Palo Alto, CA. We selected a candidate problem area based on four criteria: 1) the problem domain had to be small enough to be covered comprehensively by a relatively small knowledge base; 2) the problem domain had to be potentially useful to video display terminal (VDT) screen designers; 3) appropriate information had to be readily available in human factors guidelines, published reports, and journal articles; and 4) the problem should provide the opportunity to exercise as many of the features of NEXPERT as possible. The topic area we selected was “video display screen color”. Our goal was to produce a job performance aid (JPA) that non-human factors VDT screen designers could use to select appropriate colors for screen features. Because the system users typically have little or no formal training in human factors, the JPA has to supply color recommendations in the form of clearly stated requirements, but with the decision rationale and additional references also immediately available for users wanting more information. Using the expert system shell provided by NEXPERT, we constructed a knowledge base containing more than one hundred IF …, THEN … rules representing knowledge gained from a detailed literature review. We initially validated our expert system by posing a wide variety of hypothetical design problems and assessing its conclusions against our expectations. Based on our work so far, we have concluded that small expert systems can be useful in providing human factors expertise to system designers. We believe that increasing use of expert systems may soon lead to changes in the typical current scientific publication format to include knowledge base rules provided by the author(s).

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IMPLEMENTASI SISTEM PAKAR DIAGNOSA KERUSAKAN PADA CANON NP6650XX MENGGUNAKAN METODA DEMPSTER SHAFER

Jurnal Online Informatika ◽

10.15575/join.v1i2.36 ◽

2016 ◽

Vol 1 (2) ◽

Cited By ~ 2

Author(s):

Khaerul Manaf

Keyword(s):

Expert System ◽

Expert Systems ◽

Knowledge Base ◽

System Development ◽

Computer Software ◽

Software Tool ◽

Theory Of Knowledge ◽

Monitor Screen ◽

System Knowledge

An expert system is a computer software that has a knowledge base. Where knowledge is taken from several experts with experience working for years on a particular field of expertise. Expert systems easier to develop and specifications are not too difficult, so it can be used by computers that exist todayThe purpose of this study to design a software tool in diagnosing damage to the machine canon NP 6650XX which creates the appearance of an error code on the monitor screen machine using Dempster Shafer Method. To achieve this, research is conducted by collecting the theories associated with this machine, based on the theory of knowledge, undertake steps that expert system development, identification, conceptualization, formalization, implementation and testingThe result is a software that can provide information about damage to the machine canon NP 6650XX which such damage can lead to the appearance of an error code on the monitor screen machine. Keywords: Expert System, Knowledge, Canon Machinery, Error, Dempster Shafer.

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Expert System Diagnosis of Television Damage with Depth First Search Method Using Vb.Net Programming Language

Tech-E ◽

10.31253/te.v1i2.24 ◽

2018 ◽

Vol 1 (2) ◽

pp. 50

Author(s):

Dicky Surya Dwi Putra

Keyword(s):

Artificial Intelligence ◽

Expert System ◽

Expert Systems ◽

Knowledge Base ◽

Programming Language ◽

System Analysis ◽

Search Method ◽

Depth First Search ◽

Analysis Process ◽

System Diagnosis

The expert system is part of an artificial intelligence consisting of the knowledge and experience of an expert who is included in the knowledge base. The expert system can help someone who is still lay in solving the problem. Television is a medium of communication that receives broadcasts of moving pictures and sounds. One example of an expert system created is an expert system to diagnose television damage using the Depth First Search method using the VB.NET programming language. With the application of expert systems in diagnosing television damage, expected in the analysis process becomes faster. Expert system analysis on the damage of television can be known directly to assist in knowing what damage experienced by television and what steps to improve television. In this case, the author has consulted with an expert in the field of television damage to build a knowledge base

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