Academic literature on the topic 'EXPERT SYSTEM GENERATOR'

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Journal articles on the topic "EXPERT SYSTEM GENERATOR"

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Ho, T. L., R. A. Bayles, and E. R. Sieger. "Aircraft VSCF generator expert system." IEEE Aerospace and Electronic Systems Magazine 3, no. 4 (1988): 6–13. http://dx.doi.org/10.1109/62.860.

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Kumar, M. Sarath, and B. S. Prabhu. "Rotating Machinery Predictive Maintenance Through Expert System." International Journal of Rotating Machinery 6, no. 5 (2000): 363–73. http://dx.doi.org/10.1155/s1023621x00000348.

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Modern rotating machines such as turbomachines, either produce or absorb huge amount of power. Some of the common applications are: steam turbine-generator and gas turbine-compressor-generator trains produce power and machines, such as pumps, centrifugal compressors, motors, generators, machine tool spindles, etc., are being used in industrial applications. Condition-based maintenance of rotating machinery is a common practice where the machine's condition is monitored constantly, so that timely maintenance can be done. Since modern machines are complex and the amount of data to be interpreted is huge, we need precise and fast methods in order to arrive at the best recommendations to prevent catastrophic failure and to prolong the life of the equipment. In the present work using vibration characteristics of a rotor-bearing system, the condition of a rotating machinery (electrical rotor) is predicted using an off-line expert system. The analysis of the problem is carried out in an Object Oriented Programming (OOP) framework using the finite element method. The expert system which is also developed in an OOP paradigm gives the type of the malfunctions, suggestions and recommendations. The system is implemented in C++.
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Cheng, Edmond D. H. "Wind data generator: A knowledge-based expert system." Journal of Wind Engineering and Industrial Aerodynamics 38, no. 2-3 (1991): 101–8. http://dx.doi.org/10.1016/0167-6105(91)90032-r.

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Kato, Masami, Shiro Matsumura, Tatsuya Tosaki, et al. "Turbine Generator On-Line Monitoring and Diagnostic Expert System." IEEJ Transactions on Power and Energy 111, no. 10 (1991): 1112–20. http://dx.doi.org/10.1541/ieejpes1990.111.10_1112.

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Matsumura, S., K. Kawai, A. Kamiya, T. Koi, and K. Momoeda. "User-Friendly Expert System for Turbine/Generator Vibration Diagnosis." IFAC Proceedings Volumes 22, no. 12 (1989): 63–68. http://dx.doi.org/10.1016/s1474-6670(17)53056-6.

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Haddock, Jorge. "An expert system framework based on a simulation generator." SIMULATION 48, no. 2 (1987): 45–53. http://dx.doi.org/10.1177/003754978704800202.

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Kim, Shang-Hoon, and Sang-Yong Jung. "Optimal Design of Direct-Driven Wind Generator Using Genetic Algorithm Combined with Expert System." Journal of the Korean Institute of Illuminating and Electrical Installation Engineers 24, no. 10 (2010): 149–56. http://dx.doi.org/10.5207/jieie.2010.24.10.149.

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Yan, Chang Feng, Hui Bin Wang, Li Long Zhou, and Zhi Xin Li. "Fault Diagnosis Expert System of Turbine Generator Sets Based on Rule Reasoning and Case Reasoning." Applied Mechanics and Materials 513-517 (February 2014): 4443–48. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.4443.

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A synthetic fault diagnosis expert system for turbine generator sets based on rule based reasoning and cases based reasoning is built in this paper. The structure of synthetic fault diagnosis expert system is discussed. The rule base and case base for the fault diagnosis of expert system is established based on the domain expert knowledge and relevant fault cases of turbine generator sets. Both the inference flow and case retrieval strategy of diagnosis system are discussed in detail. Finally the expert system is verified by a given application example.
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Kaur, Gurpreet, Derminder Singh, and Rajan Aggarwal. "Geographical Information Based Expert System to Estimate Submersible Pump System Specifications." Oriental journal of computer science and technology 10, no. 2 (2017): 497–501. http://dx.doi.org/10.13005/ojcst/10.02.34.

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During past two decades, groundwater utilization has increased tremendously in the state of Punjab (India) particularly for agriculture purposes. Higher energy demand for lifting water is a result of decline in water table. Punjab is presently facing water crises which exasperate monetary conditions of small farmers, abrogate the natural value and unfavorably influence farming generation and economy of the state.In this research, an expert system was developed using Java Standard Edition 7 which provide appropriate selection of submersible pump set and required associated components such as power cable rating and size, generator capacity, ammeter rating, voltmeter rating, capacitor rating and Polyvinyl Chloride pipe diameter based on the spatial information of last 18 years (1998-2015) of ground water table for the state of Punjab. The developed system will be beneficial for the farmer’s in estimation of the required submersible pumping system and allied electrical components.
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Yoga, Herman, and R. Mahdalena Simanjorang. "Expert System for Diagnosing Damage Genset Petbow on PT.Salim Ivomas Pratama Tbk Method Using Certainty Factor (CF)." Journal Of Computer Networks, Architecture and High Performance Computing 2, no. 2 (2020): 259–62. http://dx.doi.org/10.47709/cnapc.v2i2.429.

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This study aims to design an expert system applications that are made to provide solutions to users in order to Overcome the cause of damage to the generator set. The mechanism of this program works with the Certainty Factor method, while the method used in this research is to collect information about the generator damage from experts systematically compiled into a database on a computer where the database will Determine the solution of the facts. facts on the generator sets entered into this program. The test results of this program will provide a solution to the user quickly intervening after the user Provides information to the program about the state of the generator that is interrupted or damaged.
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Dissertations / Theses on the topic "EXPERT SYSTEM GENERATOR"

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Cernik, Jacob A. "Framework for an expert system generator." Akron, OH : University of Akron, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=akron1240579896.

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Thesis (M.S.)--University of Akron, Dept. of Computer Science, 2009.<br>"May, 2009." Title from electronic thesis title page (viewed 11/18/2009) Advisor, Chien-Chung Chan; Committee members, Kathy J. Liszka, Zhong-Hui Duan; Department Chair, Wolfgang Pelz; Dean of the College, Chand Midha; Dean of the Graduate School, George R. Newkome. Includes bibliographical references.
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Cernik, Jacob A. IV. "Framework For a Rule Based Expert System Generator." University of Akron / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=akron1240579896.

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McCauley, Bob. "Expert Systems in Data Acquisition." International Foundation for Telemetering, 1987. http://hdl.handle.net/10150/615229.

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International Telemetering Conference Proceedings / October 26-29, 1987 / Town and Country Hotel, San Diego, California<br>In an Independent Research and Development (IR&D) effort, the Telemetry Systems Operation (TSO) of Computer Sciences Corporation (CSC) sought to determine the feasibility of using Artificial Intelligence (AI) techniques in a real-time processing environment. Specifically, the use of an expert system to assist in telemetry data acquisition processing was studied. A prototype expert system was implemented with the purpose of monitoring F15 Vertical Short Take Off and Landing (VSTOL) aircraft engine tests in order to predict engine stalls. This prototype expert system was implemented on a Symbolics 3670 symbolic processor using Inference Corporation's Artificial Reasoning Tool (ART) expert system compiler/generator. The Symbolics computer was connected to a Gould/SEL 32/6750 real-time processor using a Flavors, Inc. Bus Link for real-time data transfer.
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Perrott, Simon Noel. "An intelligent knowledge based system for optimising the performance of chip generator sets." Thesis, University of Greenwich, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.241632.

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Gerbaud, Laurent. "Aide à la conception des ensembles machine-convertisseur-commande : apport d'une démarche système expert." Grenoble INPG, 1993. https://hal.archives-ouvertes.fr/tel-02009245.

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L'objectif de cette thèse est de définir un outil d'aide à la conception des associations machine-convertisseur et de leurs commandes ; partir d'un cahier des charges d'une application donnée. Afin d'établir les performances de ces ensembles, le concepteur utilise dans un premier temps, un outil de simulation de ces associations avant de construire un prototype. Les premiers chapitres sont consacrés à la description d'un tel outil avec comme objectif principal de permettre une génération automatique d'équations globales et de programmes de simulation à partir d'une description modulaire de l'application. Les derniers chapitres abordent les principes d'un système expert d'aide à la conception de ces associations. Ils présentent le côté itératif et systématique de la conception et proposent un formalisme de description de la connaissance qui a permis de mettre en oeuvre un système expert où certaines étapes du processus de conception sont systématisées
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Flynn, Damian Gerard. "Expert self-tuning control for turbogenerator systems." Thesis, Queen's University Belfast, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.241393.

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Narat, Véronique. "L'aide a l'expression des contraintes d'integrite dans les systemes d'information et la generation automatique des procedures associees." Paris 6, 1988. http://www.theses.fr/1988PA066434.

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Elaboration d'un outil d'aide a la conception de systemes d'information. Un langage permettant d'exprimer les contraintes d'integrite portant sur des entites et des associations est propose a l'utilisateur. Ce langage est base sur la logique du premier ordre
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Durand, William. "Automated test generation for production systems with a model-based testing approach." Thesis, Clermont-Ferrand 2, 2016. http://www.theses.fr/2016CLF22691/document.

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Ce manuscrit de thèse porte sur le problème du test basé modèle de systèmes de production existants, tels ceux de notre partenaire industriel Michelin, l’un des trois plus grands fabricants de pneumatiques au monde. Un système de production est composé d’un ensemble de machines de production contrôlées par un ou plusieurs logiciels au sein d’un atelier dans une usine. Malgré les nombreux travaux dans le domaine du test basé modèle, l’écriture de modèles permettant de décrire un système sous test ou sa spécification reste un problème récurrent, en partie à cause de la complexité d’une telle tâche. De plus, un modèle est utile lorsqu’il est à jour par rapport à ce qu’il décrit, ce qui implique de le maintenir dans le temps. Pour autant, conserver une documentation à jour reste compliqué puisqu’il faut souvent le faire manuellement. Dans notre contexte, il est important de souligner le fait qu’un système de production fonctionne en continu et ne doit être ni arrêté ni perturbé, ce qui limite l’usage des techniques de test classiques. Pour pallier le problème de l’écriture de modèles, nous proposons une approche pour construire automatiquement des modèles depuis des séquences d’événements observés (traces) dans un environnement de production. Pour se faire, nous utilisons les informations fournies par les données échangées entre les éléments qui composent un système de production. Nous adoptons une approche boîte noire et combinons les notions de système expert, inférence de modèles et machine learning, afin de créer des modèles comportementaux. Ces modèles inférés décrivent des comportements complets, enregistrés sur un système analysé. Ces modèles sont partiels, mais également très grands (en terme de taille), ce qui les rend difficilement utilisable par la suite. Nous proposons une technique de réduction spécifique à notre contexte qui conserve l’équivalence de traces entre les modèles de base et les modèles fortement réduits. Grâce à cela, ces modèles inférés deviennent intéressant pour la génération de documentation, la fouille de données, mais également le test. Nous proposons une méthode passive de test basé modèle pour répondre au problème du test de systèmes de production sans interférer sur leur bon fonctionnement. Cette technique permet d’identifier des différences entre deux systèmes de production et réutilise l’inférence de modèles décrite précédemment. Nous introduisons deux relations d’implantation : une relation basée sur l’inclusion de traces, et une seconde relation plus faible proposée, pour remédier au fait que les modèles inférés soient partiels. Enfin, ce manuscrit de thèse présente Autofunk, un framework modulaire pour l’inférence de modèles et le test de systèmes de production qui aggrège les notions mentionnées précédemment. Son implémentation en Java a été appliquée sur différentes applications et systèmes de production chez Michelin dont les résultats sont donnés dans ce manuscrit. Le prototype développé lors de la thèse a pour vocation de devenir un outil standard chez Michelin<br>This thesis tackles the problem of testing (legacy) production systems such as those of our industrial partner Michelin, one of the three largest tire manufacturers in the world, by means of Model-based Testing. A production system is defined as a set of production machines controlled by a software, in a factory. Despite the large body of work within the field of Model-based Testing, a common issue remains the writing of models describing either the system under test or its specification. It is a tedious task that should be performed regularly in order to keep the models up to date (which is often also true for any documentation in the Industry). A second point to take into account is that production systems often run continuously and should not be disrupted, which limits the use of most of the existing classical testing techniques. We present an approach to infer exact models from traces, i.e. sequences of events observed in a production environment, to address the first issue. We leverage the data exchanged among the devices and software in a black-box perspective to construct behavioral models using different techniques such as expert systems, model inference, and machine learning. It results in large, yet partial, models gathering the behaviors recorded from a system under analysis. We introduce a context-specific algorithm to reduce such models in order to make them more usable while preserving trace equivalence between the original inferred models and the reduced ones. These models can serve different purposes, e.g., generating documentation, data mining, but also testing. To address the problem of testing production systems without disturbing them, this thesis introduces an offline passive Model-based Testing technique, allowing to detect differences between two production systems. This technique leverages the inferred models, and relies on two implementation relations: a slightly modified version of the existing trace preorder relation, and a weaker implementation proposed to overcome the partialness of the inferred models.Overall, the thesis presents Autofunk, a modular framework for model inference and testing of production systems, gathering the previous notions. Its Java implementation has been applied to different applications and production systems at Michelin, and this thesis gives results from different case studies. The prototype developed during this thesis should become a standard tool at Michelin
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Cain, Mark. "Second generation knowledge based systems in habitat evaluation." Thesis, De Montfort University, 1993. http://hdl.handle.net/2086/10711.

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Many expert, or knowledge-based, systems have been constructed in the domain of ecology, several of which are concerned with habitat evaluation. However, these systems have been geared to solving particular problems, with little regard paid to the underlying relationships that exist within a biological system. The implementation of problem-solving methods with little regard to understanding the more primary knowledge of a problem area is referred to in the literature as 'shallow', whilst the representation and utilisation of knowledge of a more fundamental kind is termed 'deep'. This thesis contains the details of a body of research exploring issues that arise from the refinement of traditional expert systems methodologies and theory via the incorporation of depth, along with enhancements in the sophistication of the methods of reasoning (and subsequent effects on the mechanisms of communication between human and computer), and the handling of uncertainty. The approach used to address this research incorporates two distinct aspects. Firstly, the literature of 'depth', expert systems in ecology, uncertainty, and control of reasoning and related user interface issues are critically reviewed, and where inadequacies exist, proposals for improvements are made. Secondly, practical work has taken place involving the construction of two knowledge based systems, one 'traditional', and the other a second generation system. Both systems are primarily geared to the problem of evaluating a pond site with respect to its suitability for the great crested newt (Triturus cristatus). This research indicates that it is possible to build a second-generation knowledge-based system in the domain of ecology, and that construction of the second generation system required a magnitude of effort similar to the firstgeneration system. In addition, it shows that, despite using different architectures and reasoning strategies, such systems may be judged as equally acceptable by endusers, and of similar accuracy in their conclusions. The research also offers guidance concerning the organisation and utilisation of deep knowledge within an expert systems framework, in both ecology and in other domains that have a similar concept-rich nature.
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Guendouze, Cheikh. "Computer assisted generation of parameters for resistance spot welding." Thesis, University of Nottingham, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.319943.

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Books on the topic "EXPERT SYSTEM GENERATOR"

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David, Jean-Marc. Second Generation Expert Systems. Springer Berlin Heidelberg, 1993.

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David, Jean-Marc, Jean-Paul Krivine, and Reid Simmons, eds. Second Generation Expert Systems. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-77927-5.

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Varlamov, Oleg. 18 examples of mivar expert systems. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1248446.

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Many years of research on mivar technologies of logical artificial intelligence have allowed us to create a new powerful, versatile and fast tool, which is called "multidimensional open gnoseological active net" — "multidimensional open gnoseological active net: MOGAN". This tool allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format, and it can be used to model cause-and-effect relationships in different subject areas and create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert systems with "Big Knowledge". The reader, after studying this tutorial, you will be able to create mivar expert system with the help of CASMI Wi!Mi. &#x0D; Designed for students, bachelors, masters and postgraduate students studying artificial intelligence methods, as well as for users, experts and specialists, creating a system of information processing and management, mivar models, expert systems, automated control systems, systems of decision support and Recommender systems.
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Fourth generation business systems: Vendor support environments and systems generation. Wiley, 1989.

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Expert systems: Introduction to first and second generation and hybrid knowledge based systems. M. Dekker, 1997.

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1958-, Balasubramanyam K. V., ed. Expert systems for structural design: A new generation. Prentice-Hall, 1988.

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Albus, James Sacra. Behavior generation in intelligent systems. U.S. Department of Commerce, Technology Administration, National Institute of Standards and Technology, 1997.

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Group, IRIS, ed. Neural and intelligent systems integration: Fifth and sixth generation integrated reasoning information systems. Wiley, 1991.

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An artificial intelligence approach to test generation. Kluwer Academic Publishers, 1987.

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Adiguzel, Rahim Ilker. Prototype report generation facility in the Data Traffic Management System. US Army Corps of Engineers, Construction Engineering Research Laboratory, 1987.

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Book chapters on the topic "EXPERT SYSTEM GENERATOR"

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Rzasa, Peter. "Steam Generator Inspection Planning Expert System." In Artificial Intelligence and Other Innovative Computer Applications in the Nuclear Industry. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1009-9_13.

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Bley, Dennis C., Jack W. Read, Stan Kaplan, James K. Liming, Neil M. Brosee, and Donald W. Hanley. "An Expert System for Diesel Generator Diagnostics." In Artificial Intelligence and Other Innovative Computer Applications in the Nuclear Industry. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1009-9_63.

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Ricard, Benoit, Bernard Monnier, Jacques Morel, Jean-Marc David, Jean-Paul Krivine, and Jean-Pierre Tiarri. "Overview of Diva: An Expert System for Turbine-Generator Diagnosis." In Artificial Intelligence and Other Innovative Computer Applications in the Nuclear Industry. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1009-9_108.

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Cacciabue, Pietro Carlo, Giovanni Guida, and Alberto Pace. "An Expert System for Modelling Operators’ Behaviour in Control of a Steam Generator." In Artificial Intelligence and Other Innovative Computer Applications in the Nuclear Industry. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1009-9_39.

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Balducelli, Claudio, and Massimo Gallanti. "Developing an Expert System for Fault Diagnosis of a Turbo Generator Group Using an OPS5 Production Rules Programming Environment." In Artificial Intelligence and Other Innovative Computer Applications in the Nuclear Industry. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1009-9_68.

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Wick, Michael R. "Second Generation Expert System Explanation." In Second Generation Expert Systems. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-77927-5_26.

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Steels, Luc. "Second Generation Expert Systems." In Expertensysteme ’87 Konzepte und Werkzeuge. Vieweg+Teubner Verlag, 1987. http://dx.doi.org/10.1007/978-3-322-94662-1_32.

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Frydenberg, Mark, and Stephen I. Gallant. "Fuzziness and expert system generation." In Uncertainty in Knowledge-Based Systems. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/3-540-18579-8_12.

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Swartout, William R., and Johanna D. Moore. "Explanation in Second Generation Expert Systems." In Second Generation Expert Systems. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-77927-5_24.

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Clancey, William J., and Monique Barbanson. "Using the System-Model-Operator Metaphor for Knowledge Acquisition." In Second Generation Expert Systems. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-77927-5_20.

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Conference papers on the topic "EXPERT SYSTEM GENERATOR"

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Xu, Shuzhen, Terry Cooper, and William Doerr. "Turbine Generator Expert System Development." In ASME 2011 Power Conference collocated with JSME ICOPE 2011. ASMEDC, 2011. http://dx.doi.org/10.1115/power2011-55194.

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This paper presents the methodology adopted for developing an expert system tool to assist in evaluating the condition of a turbine generator. Fuzzy logic is used to represent the reasoning process of an experienced engineer as well as the incomplete information inherent in this type of evaluation. The results of the evaluation inform engineers of: (a) whether the inspected unit is in good condition, (b) if not, the damage mechanisms or failure modes present, and (c) the non statistical but weighted confidence level of the evaluation.
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Xu, Shuzhen, and Enrique Susemihl. "Fuzzy Expert System Development for Electric Generator Failure Diagnostics." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-66217.

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This paper presents the development of an expert system to help engineers assess the condition of turbine generators. The expert system is designed to minimize the search and input of data in order to address the issue of the limited time available to engineers compared to the large amount of information to be investigated. To imitate the imprecise reasoning process as well as the vague information and qualitative variables inherent in this type of evaluation, fuzzy logic is used. An example of application to one failure mode, i.e., loose stator bar, is also presented.
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ZHANG, Zhi-Gang, and Jing-Sen CAO. "Research on Safety-Running Expert System for Steam-Turbine-Generator." In Proceedings of the International Conference. World Scientific Publishing Company, 2008. http://dx.doi.org/10.1142/9789812799524_0038.

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Tse, Peter W., Eugene Y. Li, Jeffery C. Chan, and Jacko T. Leung. "Automatic generator health assessment system that embedded with advanced fault diagnosis and expert system." In 2010 Prognostics and System Health Management Conference (PHM). IEEE, 2010. http://dx.doi.org/10.1109/phm.2010.5413425.

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Kim, Kil-Yoo, Young-Hwan Huh, Hee-Gon Woo, and Sung-Soo Choi. "A Hybrid Expert System for Eddy Current Test of Steam Generator Tubes." In Expert Systems and Computer Simulation in Energy Engineering: Selected Papers from the Second International Forum. Begellhouse, 1992. http://dx.doi.org/10.1615/ichmt.1992.expsystcomputsimenergengin.330.

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Kim, Kil-Yoo, Young-Hwan Huh, Hee-Gon Woo, and Sung-Soo Choi. "A HYBRID EXPERT SYSTEM FOR EDDY CURRENT TEST OF STEAM GENERATOR TUBES." In Second International Forum on Expert System and Computer Simulation in Energy Engineering. Begellhouse, 1992. http://dx.doi.org/10.1615/ichmt.1992.intforumexpsyscompsimee.600.

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Muller, H. "THE TASK AND FUNCTION OF AN EXPERT SYSTEM IN STEAM-TURBO-GENERATOR DIAGNOSTICS." In Second International Forum on Expert System and Computer Simulation in Energy Engineering. Begellhouse, 1992. http://dx.doi.org/10.1615/ichmt.1992.intforumexpsyscompsimee.320.

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Ning Yang, Shaocheng Zhang, Yaoliang Xu, Wanjian Zhao, and Yi Zhu. "An expert system for vibration fault diagnosis of large steam turbine generator set." In 2011 3rd International Conference on Computer Research and Development (ICCRD). IEEE, 2011. http://dx.doi.org/10.1109/iccrd.2011.5764118.

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Muller, H. "The Task and Function of an Expert System in Steam-Turbo-Generator Diagnostics." In Expert Systems and Computer Simulation in Energy Engineering: Selected Papers from the Second International Forum. Begellhouse, 1992. http://dx.doi.org/10.1615/ichmt.1992.expsystcomputsimenergengin.240.

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Shang-Hoon Kim and Sang-Yong Jung. "Optimal design of direct-driven wind generator using Genetic Algorithm combined with Expert System." In 2010 14th Biennial IEEE Conference on Electromagnetic Field Computation (CEFC 2010). IEEE, 2010. http://dx.doi.org/10.1109/cefc.2010.5481699.

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Reports on the topic "EXPERT SYSTEM GENERATOR"

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Williamson, Douglas Alan. Expert System analysis of non-fuel assembly hardware and spent fuel disassembly hardware: Its generation and recommended disposal. Office of Scientific and Technical Information (OSTI), 1991. http://dx.doi.org/10.2172/10185549.

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Grace, Robert, and Ryan Wiser. Transacting generation attributes across market boundaries: Compatible information systems and the treatment of imports and exports. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/806138.

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Doo, Johnny. Unsettled Issues Concerning the Opportunities and Challenges of eVTOL Applications during a Global Pandemic. SAE International, 2020. http://dx.doi.org/10.4271/epr2020022.

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Abstract:
Electric vertical takeoff and landing (eVTOL) aircraft technology has developed beyond the traditional aviation industry and now influences the creation of new and novel transportation applications. Some experts even suggest on-demand eVTOL logistics capabilities could be harnessed by crisis response teams to c ombat a future pandemic. The lessons of the COVID-19 crisis highlighted the challenges of managing a global pandemic response due to the difference in regional and local resources, culture, and political systems. Although there may not be a uniform crisis management strategy that the world can agree on, next-generation vertical flight vehicles could be used to distribute limited medical equipment, supplies, and personnel to hot spots faster than conventional aircraft or ground vehicles. However, creating this capability is not easy. This SAE EDGE™ Research Report by Johnny Doo addresses the opportunities and challenges of establishing an eVTOL fleet, including deployment, supporting infrastructure, and fleet management.
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