Academic literature on the topic 'Expert system'

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Journal articles on the topic "Expert system"

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NCC Ltd. "Expert system helps experts." Knowledge-Based Systems 1, no. 4 (September 1988): 250. http://dx.doi.org/10.1016/0950-7051(88)90040-8.

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Priyanka, Nalawade, Mane Gayatri, and Jankar Priyanka Kurde Ashwini Prof Balwante Shrikrishna Shivrai. "Expert Finding System." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 1993–98. http://dx.doi.org/10.31142/ijtsrd11594.

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W, Yunanri, Doddy Teguh Yuwono, and Ika Safitri Windarti. "SYSTEMATIC OF EXPERT SYSTEM BASE ON SOFTWARE AND CALCULATION METHOD." Jurnal Informatika, Teknologi dan Sains 2, no. 1 (February 20, 2020): 1–6. http://dx.doi.org/10.51401/jinteks.v2i1.552.

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The expert system is a system that seeks to adopt human knowledge into technology, so that technology can solve problems as is usually done by experts. A good expert system is designed to solve a particular problem by imitating the work of the experts. With expert systems, the layman can solve quite complicated problems, because in fact the problem can only be solved with the help of experts. For experts, the expert system will also assist its activities as a highly experienced assistant. Currently there are many studies that raise cases about expert systems. This study aims to create systematic on expert systems based on a collection of expert system cases and classify them based on the tools used, implementation types and frequently used methods.
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Martin, A., and RKH Law. "Expert system for selecting expert system shells." Information and Software Technology 30, no. 10 (December 1988): 579–86. http://dx.doi.org/10.1016/0950-5849(88)90114-0.

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McClure, Janice E. "DEVELOPMENT OF AN EXPERT SYSTEM." HortScience 26, no. 6 (June 1991): 795B—795. http://dx.doi.org/10.21273/hortsci.26.6.795b.

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The development of expert systems in agriculture consists of many steps such as problem definition, selection of experts, audience considerations, knowledge representation, coding, testing, and feedback. The problem definition and selection of experts for the problem domain are the foundation of a working system. Audience definition, economics and goal setting are areas that must be documented before knowledge engineering. Knowledge representation methods and system conceptual layout are the next level of development. The use of the user feedback and field testing data to improve the system are often overlooked. Benefits of expert systems for on farm decision making include education, efficiency, and adaption to changing regulations. Many aspects of agricultural expert systems are similar to traditional expert systems; yet special problem inherent in agriculture make the development interesting and challenging.
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Martin, Gilles G., James Lienhart, R. Anand, Edward J. Dudewicz, and George C. Levy. "From Statistical-Expert-System to Expert-Statistical-System." American Journal of Mathematical and Management Sciences 9, no. 3-4 (February 1989): 273–97. http://dx.doi.org/10.1080/01966324.1989.10737267.

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Ostrowsky, Marianne F., and Ruth C. Swezey. "An expert system shell: Expert system environment/VM." ISA Transactions 28, no. 1 (January 1989): 9–14. http://dx.doi.org/10.1016/0019-0578(89)90049-9.

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Mauliani, Asri, and Andronias Siregar. "SISTEM PAKAR PENYELEKSIAN KULIT ULAR UNTUK EKSPOR MENGGUNAKAN METODE FORWARD CHAINING PADA CV. ALONA JAYA." Akrab Juara : Jurnal Ilmu-ilmu Sosial 6, no. 4 (November 6, 2021): 138. http://dx.doi.org/10.58487/akrabjuara.v6i4.2039.

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Snake skin is one type of reptile skin that has now been used as a commodity trade with a fairly high price. Snake skin that is ripe for export certainly experienced some process first, one of the process is the selection to know the skin into the category class I, II or III. CV. Alona Jaya is a company engaged in the export of reptile skin. Human resources owned CV. Alona Jaya not all experts in the field of skin selection, so still need the help of experts in handling the process. Expert system applications capable of imitating the work of an expert in various fields, one of them is snake skin selection. This expert system is built using forward chaining method, as a search technique that starts from a known fact to reach a goal. The design of this application using UML and Visual Basic programming language with Microsoft Access database as its application. This research produces an expert system application that can be used in snake skin selection for export, so it can help human resources who are not experts at the time of skin selection
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Hutapea, Mei Melan Rut Sartika, and R. Mahdalena Simanjorang. "Expert System to Diagnose Malaria With Bayes Method." Journal Of Computer Networks, Architecture and High Performance Computing 2, no. 1 (January 1, 2020): 88–92. http://dx.doi.org/10.47709/cnapc.v2i1.363.

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Malaria is a deadly disease. The disease is caused by a virus that is transmitted through the bite plasmadium Anopheles mosquito tropics. , Indonesia is an area that has a tropical climate so that malaria prevalent in Indonesia. Many public cloud lack of knowledge about the symptoms of malaria because malaria disease symptoms similar to the usual feverish illness. If the disease is not handled seriously can lead to death. From the above explanation makes the excuse needed one expert system that can help people diagnose malaria by looking at symptoms, and later this expert system can explain and diagnose whether a disease malaria or not. In the expert system there are several methods used to menagani a problem. With the solution given institute Bayes Method in helping to diagnose diseases, the expert system that can help people diagnose malaria by looking at symptoms, and later this expert system can explain and diagnose whether a disease malaria or not. Expert System is generally defined as a system that is able to region contribute to solving or handling problems. Expert System is not intended to replace the expert, but to help and support experts. Bayesian methods can diagnose simple encoding and faster calculation. expert system that can help people diagnose malaria by looking at symptoms, and later this expert system can explain and diagnose whether a disease malaria or not. Expert System is generally defined as a system that is able to region contribute to solving or handling problems. Expert System is not intended to replace the expert, but to help and support experts. Bayesian methods can diagnose simple encoding and faster calculation. expert system that can help people diagnose malaria by looking at symptoms, and later this expert system can explain and diagnose whether a disease malaria or not. Expert System is generally defined as a system that is able to region contribute to solving or handling problems. Expert System is not intended to replace the expert, but to help and support experts. Bayesian methods can diagnose simple encoding and faster calculation. Expert System is generally defined as a system that is able to region contribute to solving or handling problems. Expert System is not intended to replace the expert, but to help and support experts. Bayesian methods can diagnose simple encoding and faster calculation. Expert System is generally defined as a system that is able to region contribute to solving or handling problems. Expert System is not intended to replace the expert, but to help and support experts. Bayesian methods can diagnose simple encoding and faster calculation.
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Arisandi, Diki. "PENGUJIAN RULE PADA SISTEM PAKAR PENANGANAN CEDERA OLAHRAGA BOLA BASKET." Rabit : Jurnal Teknologi dan Sistem Informasi Univrab 1, no. 2 (July 10, 2016): 94–103. http://dx.doi.org/10.36341/rabit.v1i2.27.

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Expert system is a system created using computers that aims to imitate experts in solving problems. This expert system was built to deal with injury problems in basketball, including how to treat them. Before use, expert systems must be tested first so that no errors occur when used. Testing uses the black-box method, which means testing the system output based on input. In addition, the rules and inference in this expert system are also tested so that each stage of consultation produces a solution that is in accordance with the knowledge of the experts. After going through the testing process, it is hoped that this expert system can be used by the experts themselves and other users in overcoming the problem of injury in basketball.
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Dissertations / Theses on the topic "Expert system"

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Kovalenko, K. "Expert system." Thesis, Видавництво СумДУ, 2012. http://essuir.sumdu.edu.ua/handle/123456789/26069.

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Beartusk, Brodi J. (Brodi Jay). "An expert system assistant for gathering expert knowledge." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/40573.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.
Includes bibliographical references (leaf 49).
by Brodi J. Beartusk.
M.Eng.
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Erturk, Alper. "An expert system for reward systems design." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2000. http://handle.dtic.mil/100.2/ADA383532.

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Thesis (M.S. in Information Technology Management and M.S. in Systems Management) Naval Postgraduate School, Sept. 2000.
Thesis advisor(s): Jansen, Erik; Nissen, Mark E. Includes bibliographical references (p. 93-94). Also available online.
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Sachdev, Sharad. "Temporal expert system shell." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ33826.pdf.

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Huang, Shi-Ming. "An integrated expert database system." Thesis, University of Sunderland, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.385011.

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Zoorob, Riad J. "S.E.S., a simulation expert system." Virtual Press, 1994. http://liblink.bsu.edu/uhtbin/catkey/897507.

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The continuous increase in the cost of building real life projects, the high cost of researches concerning a project and the urgent demands for the project to be delivered in a short period of time have urged researchers to find a new scheme of programming in which they would be able to simulate or emulate the real life activities and projects using a computer and a procedural language. But such a scheme of programming was lengthy, tedious and costly. Therefore, it was necessary to find a specialized simulation software that would save the programmer's time and effort on the one hand and would save the client's money on the other. A number of simulation software were developed recently which contributed greatly to the solutions of the simulation problems. However, none of these languages possessed the completeness nor the independence of the use of other tools or procedural languages to compensate for their deficiencies.In this paper I have proposed a number of new ideas aimed to improve the simulation languages in general, and have implemented a number of these ideas in a software package. Chapter one describes the simulation model and the basic concepts of simulation. Chapter two describes briefly the advantages and disadvantages of using simulation software. Also it outlines the limitations of currently used simulation packages. Finally, it suggests new ideas and expectations of a complete simulation package. Chapter three describes the simulation package prototype S. E. S. and gives some implementations. Chapter four explains the basic differences between S. E. S. and SLAM II and shows areas for further research.
Department of Computer Science
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Dybowski, Richard. "A steroid profiling expert system." Thesis, University of Leeds, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.235634.

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Karandikar, Swanandesh S. "Expert system applications in architecture." Thesis, Virginia Tech, 1989. http://hdl.handle.net/10919/44116.

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This study proposes an Architectural Expert System (AES) to act as a design partner for architectural designers. Architectural designers are faced with a very complex task of searching a solution space, which is a labyrinth of several domains ranging from social to cultural, and from aesthetic to scientific. With the number of domains come a number of experts of that domain. After progressing through tedious analytical procedures involving the physical principles in architecture, and applying the knowledge of experience, the experts are able to convert the raw data into useful design guidelines.

Research in the field of artificial intelligence has developed techniques which can capture such expertise in a computer program, which then emulates the expert. This technology is know as Expert System (ES). This study has used this technology to develop a system to aid architectural design. An AES model is derived from literature review. As the nature of a system based on this model is complex and would require custom built software, an alternative is developed based on the derived model. Based on this alternative, a prototype is developed for energy audit and energy conservation by capturing the expertise of an energy conscious design expert. This prototype module is one component of the sub-system of AES and provides an example for further modules. Various areas such as design, architecture, artificial intelligence and expert systems technology, and energy conscious design and energy conservation converge, and become parts of this study.
Master of Science

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Diaz, Suarez Carlos Fernando. "Basement failure diagnosis expert system /." The Ohio State University, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=osu148784154827184.

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Bradshaw, John. "The P.R.O. expert system shell." Thesis, Rhodes University, 1987. http://hdl.handle.net/10962/d1006302.

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This thesis reports the research which led to the development of the P.R .O. Expert System Shell. The P.R.O . System is primarily, though not exclusively , designed for use in ecological domains. In the light of two specific expert systems, The RCS (River Conservation Status) and the Aquaculture Systems, which were developed as part of this research, a number of areas of importance have been identified. The most significant of these is the need to handle uncertainty effectively. The style of knowledge representation to be implemented also plays an important role. After consulting the relevant literature and the available microcomputer expert system shells, a number of ideas have been included in the P.R.O. System. The P.R.O . System is a backward chaining, production system based expert system shell. It embodies a simple but effective method of handling uncertainty. An important feature of this method is that it takes cognizance of the different relative importances of the conditions which need to be satisfied before a conclusion can be reached. The knowledge base consists of more than rules and questions. It also contains meta-knowledge, which is used by the inference engine. The P.R.O. System has been designed to be of practical use. Its strongest recommendations are therefore, that the two non-trivial systems which have been implemented in it, have been accepted by the experts and their peers as systems which produce good, accurate answers .
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Books on the topic "Expert system"

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Bolc, Leonard, and Michael J. Coombs, eds. Expert System Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-83314-4.

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University of Manchester. Regional ComputerCentre., ed. SAVOIR expert system. Manchester: UMRCC, 1987.

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Miller, Howard W. Expert system technology. Byfield, Mass. (136 Orchard St., Byfield, 01922-1605): Information Technology Institute, 1993.

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1934-, Bolc Leonard, Coombs M. J, and Bock C, eds. Expert system applications. Berlin: Springer-Verlag, 1988.

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Jones, O. Acupuncture expert system. Manchester: University of Manchester, Department of Computer Science, 1997.

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1943-, Dillon Tharam S., and Laughton M. A, eds. Expert system applications in power systems. New York: Prentice Hall, 1990.

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S, Dillon Tharam, and Laughton Michael A, eds. Expert system applications in power systems. New York: Prentice Hall, 1990.

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United States. National Aeronautics and Space Administration., ed. ICE system, interruptible control expert system. [Cleveland, Ohio]: Dept. of Computer Engineering and Science, Case Western Reserve University, 1990.

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1957-, Liebowitz Jay, ed. Expert system applications to telecommunications. New York: Wiley, 1988.

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Erturk, Alper. An expert system for reward systems design. Monterey, Calif: Naval Postgraduate School, 2000.

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Book chapters on the topic "Expert system"

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Nahler, Gerhard. "expert system." In Dictionary of Pharmaceutical Medicine, 72. Vienna: Springer Vienna, 2009. http://dx.doi.org/10.1007/978-3-211-89836-9_534.

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Weik, Martin H. "expert system." In Computer Science and Communications Dictionary, 552. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_6580.

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Chakrabarti, Dilip Kumar, and Prabhat Mittal. "Expert System." In Plant Disease Forecasting Systems, 67–82. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1210-0_7.

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Bell, Charles. "Database System Internals." In Expert MySQL, 455–63. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4660-2_11.

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Balas, Marius M., and Robert A. Boran. "Basic Expert System." In Soft Computing Applications, 12–17. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62521-8_2.

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Shinskey, F. G. "Distillation Expert System." In Practical Distillation Control, 272–90. New York, NY: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4757-0277-4_13.

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Weik, Martin H. "expert system shell." In Computer Science and Communications Dictionary, 552. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_6581.

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Norris, Donald J. "Expert System Demonstrations." In Beginning Artificial Intelligence with the Raspberry Pi, 49–76. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2743-5_3.

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Tebbutt, Colin D. "The Expert System." In Advances in Industrial Control, 41–50. London: Springer London, 1994. http://dx.doi.org/10.1007/978-1-4471-2104-6_4.

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Metzing, Detlev. "Expert System: Plants." In Ecological Studies, 433–43. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-12539-3_26.

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Conference papers on the topic "Expert system"

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Song, Il-Yeol, and Joseph LaGue. "Predicting expert system success: an expert system for expert systems." In the 1990 ACM SIGBDP conference. New York, New York, USA: ACM Press, 1990. http://dx.doi.org/10.1145/97709.97717.

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Westrom, George B. "Expert imaging system." In Lausanne - DL tentative, edited by Murat Kunt. SPIE, 1990. http://dx.doi.org/10.1117/12.24178.

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Dowell, Laurie, Jack Gary, Bill Illingworth, and Tom Sargent. "Capital Expert System." In Applications of Artificial Intelligence V, edited by John F. Gilmore. SPIE, 1987. http://dx.doi.org/10.1117/12.940599.

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Matsumoto, N., H. Kuraoka, N. Ohka, M. Ohba, and T. Tabe. "Expert Antiskid System." In Robotics and IECON '87 Conferences, edited by Victor K. Huang. SPIE, 1987. http://dx.doi.org/10.1117/12.943267.

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Al-Taani, Ahmad T., Sallam Abualhaija, Susanne Ramadan, and Izza Abuhaija. "Poetry expert system." In the 3rd International Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2222444.2222459.

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Khaksari, Gholam H. "Expert diagnostic system." In the first international conference. New York, New York, USA: ACM Press, 1988. http://dx.doi.org/10.1145/51909.51915.

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Afgan, Naim Hamdia, A. G. Bloch, P. Radovanovic, Yu A. Zhurovlev, and E. I. Gorb. "Boiler Expert System." In Expert Systems and Computer Simulation in Energy Engineering: Selected Papers from the Second International Forum. Connecticut: Begellhouse, 1992. http://dx.doi.org/10.1615/ichmt.1992.expsystcomputsimenergengin.310.

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Afgan, Naim Hamdia, A. G. Bloch, P. Radovanovic, Yu A. Zhurovlev, and E. I. Gorb. "BOILER EXPERT SYSTEM." In Second International Forum on Expert System and Computer Simulation in Energy Engineering. Connecticut: Begellhouse, 1992. http://dx.doi.org/10.1615/ichmt.1992.intforumexpsyscompsimee.340.

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Cheng, Stephen C., John Comella, and Phaih-Lan Law. "Expert's Toolkit: An Expert System Shell For Building Diagnostic Systems." In SPIE 1989 Technical Symposium on Aerospace Sensing, edited by Mohan M. Trivedi. SPIE, 1989. http://dx.doi.org/10.1117/12.969268.

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Cao, Hong, and Mei Ma. "A Diagnostic Expert System for Oil Systems of Aeroengines." In ASME 1993 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/93-gt-349.

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DIAG, a diagnostic expert system for oil systems of aeroengines, is presented in this paper. Using artificial intelligence, DIAG, which simulates the role of human experts in solving problems, can solve the complicated problems in diagnosing the faults and failures of oil systems of gas turbine engines. The paper concentrates on the design of DIAG as well as the process of handling the complex relation and uncertainty of problems. It also includes graphic subsystem and data subsystem. It is affirmed by the expected goal of diagnosing the faults and failures of oil system and engine of CFM56 engine on Boeing 737–300 airplane.
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Reports on the topic "Expert system"

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Fong, Elizabeth N., and Christopher E. Dabrowski. A prototype expert system :. Gaithersburg, MD: National Bureau of Standards, 1988. http://dx.doi.org/10.6028/nbs.ir.88-3689.

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Maher, John C., Robert B. Bailey, Richard M. Graves, and William E. Mathews. Living Expert System (LEXSYS). Volume 4. Fort Belvoir, VA: Defense Technical Information Center, April 1989. http://dx.doi.org/10.21236/ada210843.

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Brandt, Alan, and Sarah Rennie. Expert System for Mine Burial Prediction. Fort Belvoir, VA: Defense Technical Information Center, September 2004. http://dx.doi.org/10.21236/ada613046.

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Jasperson, William H., and David E. Venne. A Regional Weather Forecasting Expert System. Fort Belvoir, VA: Defense Technical Information Center, June 1996. http://dx.doi.org/10.21236/ada316130.

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Friedman-Hill, E. J. Jess, the Java expert system shell. Office of Scientific and Technical Information (OSTI), November 1997. http://dx.doi.org/10.2172/565603.

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Brandt, Alan. Expert System for Mine Burial Prediction. Fort Belvoir, VA: Defense Technical Information Center, September 2003. http://dx.doi.org/10.21236/ada628131.

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Gahm, Gregory A. Expert System Utilization for Behavioral Health. Fort Belvoir, VA: Defense Technical Information Center, June 2003. http://dx.doi.org/10.21236/ada421142.

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Osella, Stephen A. Expert Control System Shell, version 1.0:. Gaithersburg, MD: National Institute of Standards and Technology, 1995. http://dx.doi.org/10.6028/nist.ir.5601.

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Peak, J. E. AESOP 2.1 Expert System Users Manual. Fort Belvoir, VA: Defense Technical Information Center, March 1991. http://dx.doi.org/10.21236/ada239260.

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Szatkowski, Gerry. Advanced Launch System (ALS) Space Transportation Expert System Study. Fort Belvoir, VA: Defense Technical Information Center, March 1991. http://dx.doi.org/10.21236/ada248708.

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