Techniques for capturing expert knowledge: an expert systems/hypertext approach

1990 ◽  
Author(s):  
Lawrence Lafferty ◽  
Albert M. Koller, Jr. ◽  
Greg Taylor ◽  
Robin S. Schumann ◽  
Randy Evans
Keyword(s):  
Expert Systems ◽  
Expert Knowledge

Artificial intelligence: a new tool for forest management

1990 ◽  
Vol 20 (4) ◽  
pp. 428-437 ◽  
Author(s):  
Peter Kourtz
Keyword(s):  
Artificial Intelligence ◽  
Forest Management ◽  
Expert Systems ◽  
Computer Science ◽  
Solution Structure ◽  
Visual Recognition ◽  
Knowledge Engineering ◽  
Expert Knowledge ◽  
Low Cost ◽  
Process Models

Articicial intelligence is a new science that deals with the representation, automatic acquisition, and use of knowledge. Artificial intelligence programs attempt to emulate human thought processes such as deduction, inference, language, and visual recognition. The goal of artificial intelligence is to make computers more useful for reasoning, planning, acting, and communicating with humans. Development of artificial intelligence applications involves the integration of advanced computer science, psychology, and sometimes robotics. Of the subfields that artificial intelligence can be broken into, the one of most immediate interest to forest management is expert systems. Expert systems involve encoding knowledge usually derived from an expert in a narrow subject area and using this knowledge to mimic his decision making. The knowledge is represented usually in the form of facts and rules, involving symbols such as English words. At the core of these systems is a mechanism that automatically searches for and pieces together the facts and rules necessary to solve a specific problem. Small expert systems can be developed on common microcomputers using existing low-cost commercial expert shells. Shells are general expert systems empty of knowledge. The user merely defines the solution structure and adds the desired knowledge. Larger systems usually require integration with existing forestry data bases and models. Their development requires either the relatively expensive expert system development tool kits or the use of one of the artificial intelligence development languages such as lisp or PROLOG. Large systems are expensive to develop, require a high degree of skill in knowledge engineering and computer science, and can require years of testing and modification before they become operational. Expert systems have a major role in all aspects of Canadian forestry. They can be used in conjunction with conventional process models to add currently lacking expert knowledge or as pure knowledge-based systems to solve problems never before tackled. They can preserve and accumulate forestry knowledge by encoding it. Expert systems allow us to package our forestry knowlege into a transportable and saleable product. They are a means to ensure consistent application of policies and operational procedures. There is a sense of urgency associated with the integration of artificial intelligence tools into Canadian forestry. Canada must awaken to the potential of this technology. Such systems are essential to improve industrial efficiency. A possible spin-off will be a resource knowledge business that can market our forestry knowledge worldwide. If we act decisively, we can easily compete with other countries such as Japan to fill this niche. A consortium of resource companies, provincial resource agencies, universities, and federal government laboratories is required to advance this goal.

scholarly journals Sistem Diagnosa Penyakit THT Pada Balita Menggunakan Dempster Shafer

2018 ◽  
Vol 3 (1) ◽  
pp. 27
Author(s):  
Maura Widyaningsih
Keyword(s):  
Decision Making ◽  
Problem Solving ◽  
Expert Systems ◽  
Expert Knowledge ◽  
Computing Systems ◽  
Knowledge Based System ◽  
Forward Chaining ◽  
Knowledge Based ◽  
Rule Changes ◽  
Auxiliary Program

Computer field supports the existence of auxiliary program in medical development that is expert knowledge-based system, this system is one branch of Artifical Intellegence (AI). Expert systems are knowledge in learning about estimation or decision-making ability of an expert. Problem solving in the identification of a disease by using auxiliary program is needed a method and concept. Calculation techniques in computing systems are so important, given the level of need for information and the settlement of cases quickly.The results of the study are expert applications that assist in providing results of diagnosis of symptoms managed  the system, with inference using forward chaining, and reasioning with Dempster Shafer. Dempster Shafer's method is not monotonous in solving uncertainty problems, due to the addition or subtraction of new facts. Rule changes will occur, allowing the system to do the work of an expert.Data changes will occur both to diseases, symptoms, solutions and rules, allowing the system to do the work of an expert. The results of manual calculations with the system gives results in accordance with the application of Dempster Shafer method. Management of rules in the database facilitates the search for symptoms within the system.

Expert Systems in Distance Education

2018 ◽  
pp. 1410-1423
Author(s):  
Duygu Mutlu-Bayraktar ◽  
Esad Esgin
Keyword(s):  
Artificial Intelligence ◽  
Distance Education ◽  
Natural Language ◽  
Expert Systems ◽  
Expert Knowledge ◽  
Computer Systems ◽  
Educational Environments ◽  
Artificial Environment ◽  
Present Solution ◽  
Definition Of

Computers have been used in educational environments to carry out applications that need expertise, such as compiling, storing, presentation, and evaluation of information. In some teaching environments that need expert knowledge, capturing and imitating the knowledge of the expert in an artificial environment and utilizing computer systems that have the ability to communicate with people using natural language might reduce the need for the expert and provide fast results. Expert systems are a study area of artificial intelligence and can be defined as computer systems that can approach a problem for which an answer is being sought like an expert and present solution recommendations. In this chapter, the definition of expert systems and their characteristics, information about the expert systems in teaching environments, and especially their utilization in distance education are given.

Pest Plant Disease Prevention and Identification System Using Certainty Factor Method

2018 ◽  
Vol 7 (3.2) ◽  
pp. 763 ◽  
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.  

scholarly journals Application of expert systems in diagnostics, management and logistics

2008 ◽  
Vol 15 (3) ◽  
pp. 86-91
Author(s):  
Zbigniew Korczewski
Keyword(s):  
Expert Systems ◽  
Expert Knowledge ◽  
Knowledge Codification ◽  
Organisation Structure ◽  
Object Attribute ◽  
Attribute Value

Application of expert systems in diagnostics, management and logistics There has been demonstrated base terms concerning expert systems and analysis of their organisation structure. Some possibilities of the expert knowledge codification worked out on the basis of different application of the object-attribute-value triplets have been presented as well.

Expert systems for management: Research and applications

1984 ◽  
Vol 9 (4) ◽  
pp. 153-162 ◽  
Author(s):  
Robert W. Blanning
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Real World ◽  
Expert Knowledge ◽  
Management Systems ◽  
Management Research ◽  
System Technology ◽  
Real World Data ◽  
Subjective Data ◽  
World Data

Management scientists and systems designers have long recognized that in some cases objective real world data con tained in their models and systems should be supplemented by subjective data elicited from experienced managers. The recent but growing application of expert system technology to mana gement problems is providing a framework for capturing and using expert knowledge in management systems. In this paper we identify fruitful areas for research and application of expert systems in management.

Expert knowledge, expert systems and commercial interests

Omega ◽  
1985 ◽  
Vol 13 (5) ◽  
pp. 407-418 ◽  
Author(s):  
Elizabeth Pollitzer ◽  
John Jenkins
Keyword(s):  
Expert Systems ◽  
Expert Knowledge

The Application of Human Factors to the Development of Expert Systems for Advanced Cockpits

1987 ◽  
Vol 31 (12) ◽  
pp. 1388-1392 ◽  
Author(s):  
Mica R. Endsley
Keyword(s):  
Human Factors ◽  
Expert Systems ◽  
Situational Awareness ◽  
Expert Knowledge ◽  
Systems Development ◽  
System Evaluation ◽  
Design And Implementation ◽  
Successful Design ◽  
Role Allocation ◽  
Selection Of

Expert system applications must be carefully selected, designed and integrated into the cockpit based on a full understanding of the pilot's tasks, requirements, and capabilities. In this paper, expert systems development issues in the following areas are identified and addressed utilizing processes, methodologies and knowledge from the human factors field: the selection of systems to automate, the elicitation of expert knowledge from pilots, role allocation between the pilot and the system, system design issues, and system evaluation. Considerations of pilot workload, situational awareness, performance and pilot acceptance are considered key to the successful design and implementation of expert systems which will truly enhance the pilot in the performance of his tasks.

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