Abstract
In this paper, the methodology for an intelligent assistant for power plants is presented. Multiagent systems technology and data mining techniques are combined to enhance the intelligence of the proposed application, mainly in two aspects: increase the reliability of input data (sensor validation and false measurement replacement) and generate new control monitoring rules. Various classification algorithms are compared. The performance of the application, as tested via simulation experiments, is discussed.
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ABB Group, Products & Services, http://www.abb.com/ProductGuide
Flynn, D. (ed.): Thermal Power Plant Simulation and Control. IEE, London (2003)
Hadjiski, M., Boshnakov, K., Christova, N., Terziev, A.: Multi Agent Simulation in Inference Evaluation of Steam Boiler Emission. In: 19th European Conference on Modeling and Simulation, pp. 552–557. Riga, Latvia (2005)
Ma, Z., Iman, F., Lu, P., Sears, R., Kong, L., Rokanuzzaman, A.S., McCollor, D.P., Benson, S.A.: A Comprehensive Slagging and Fouling Prediction Tool for Coal-Fired Boilers and its Validation/Application. Fuel Process. Technol. 88, 1035–1043 (2007)
Frank, P.: Fault Diagnosis in Dynamic Systems Using Analytical and Knowledge Based Redundancy- a Survey and Some New Results. Automatica 26, 459–470 (1990)
Eryurek, E., Upadhyaya, B.R.: Sensor Validation for Power Plants Using Adaptive Backpropagation Neural Network. IEEE Trans. Nucl. Science 37, 1040–1047 (1990)
Ibarguengoytia, P.H., Vadera, S., Sucar, L.E.: A Probabilistic Model for Information and Sensor Validation. The Computer Journal 49(1), 113–126 (2006)
Athanasopoulou, C., Chatziathanasiou, V.: Intelligent System for Identification and Replacement of Faulty Sensor Measurements in Thermal Power Plants (IPPAMAS: Part 1). Expert Systems With Applications 36(5), 8750–8757 (2009)
Shim, J.: Past, Present, and Future of Decision Support Technology. Decision Support Systems 33(2), 111–126 (2002)
Vahidov, R.: Intermediating User-DSS Interaction with Autonomous Agents. IEEE Trans. on Systems, Man, and Cybernetics 35(6), 964–970 (2005)
Gao, S., Xu, D.: Conceptual Modeling and Development of an Intelligent Agent-Assisted Decision Support System for Anti-money Laundering. Expert Systems with Applications 36, 1493–1504 (2009)
Lucas, C., Zia, M.A., Shirazi, M.R.A., Alishahi, A.: Development of a Multi-agent Information Management System for Iran Power Industry-A Case Study. In: Power Tech 2001 Proceedings, vol. 3. IEEE, Porto (2001)
Pechoucek, M., Marik, V.: Industrial Deployment of Multi-agent Technologies: Review and Selected Case Studies. Auton Agent Multi-Agent Syst. 17, 397–431 (2008)
Athanasopoulou, C., Chatziathanasiou, V.: Prototype For Optimizing Power Plant Operation. In: Mangina, E., Carbo, J., Molina, J. (eds.) Agent-based Ubiquitous Computing. Atlantis Press (2009)
Kopanas, I., Avouris, N.M., Daskalaki, S.: The Role of Domain Knowledge in a Large Scale Data Mining Project. In: Vlahavas, I.P., Spyropoulos, C.D. (eds.) SETN 2002. LNCS (LNAI), vol. 2308, pp. 288–299. Springer, Heidelberg (2002)
Arranz, A., Cruz, A., Sanz-Bobi, M.A., Ruiz, P., Coutino, J.: DADICC: Intelligent System for Anomaly Detection in a Combined Cycle Gas Turbine Plant. Expert Systems with Applications 34, 2267–2277 (2008)
Mangina, E.: Application of Intelligent Agents in Power Industry: Promises and Complex Issues. In: Marik, V., Muller, J., Pechoucek, M. (eds.) CEEMAS 2003. LNCS (LNAI), vol. 2691, pp. 564–574. Springer, Heidelberg (2003)
Soldatos, J., Pandis, I., Stamatis, K., Polymenakos, L., Crowley, J.: Agent Based Middleware Infrastructure for Autonomous Context-Aware Ubiquitous Computing Services. Computer Communic. 30, 577–591 (2007)
Symeonidis, A., Mitkas, P.A.: Agent Intelligence Through Data Mining. Springer, New York (2005)
Shreiber, G., Akkermans, H., Anjewierden, A., de Hoog, R., Shadbolt, N., Van de Velde, W., Wielinga, B.: Knowledge Engineering and Management: the CommonKADS methodology. MIT Press, Cambridge (2000)
Iglesias, C.A., Garijo, M.: The Agent-Oriented Methodology MASCommonKADS. In: Henderson-Sellers, B., Giorgini, P. (eds.) Agent-Oriented Methodologies, pp. 46–78. IDEA Group Publishing (2005)
Witten, I., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)
JADE, http://jade.tilab.com
Agent Academy, https://sourceforge.net/projects/agentacademy
Hall, M., Holmes, G., Frank, E.: Generating Rule Sets from Model Trees. In: Foo, N.Y. (ed.) AI 1999. LNCS (LNAI), vol. 1747, pp. 1–12. Springer, Heidelberg (1999)
Bishop, C.M.: Neural Networks for pattern recognition. Oxford University Press, New York (1995)
Aha, D.W., Kibler, D., Albert, M.: Instance-Based Learning Algorithms. Machine Learning 6, 37–66 (1991)
Cleary, J., Trigg, L.: K*: An Instance-Based Learner Using an Entropic Distance Measure. In: 12th Inter. Confer. on Machine learning, pp. 108–114 (1995)
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Athanasopoulou, C., Chatziathanasiou, V. (2009). Enhancing Agent Intelligence through Data Mining: A Power Plant Case Study. In: Cao, L., Gorodetsky, V., Liu, J., Weiss, G., Yu, P.S. (eds) Agents and Data Mining Interaction. ADMI 2009. Lecture Notes in Computer Science(), vol 5680. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03603-3_10
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DOI: https://doi.org/10.1007/978-3-642-03603-3_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03602-6
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