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2nd New Zealand Two-Stream International Conference on Artificial Neural Networks and Expert Systems (ANNES '95)
Hybrid Systems for Prediction - A Case Study of Predicting Effluent Flow to a Sewage Plant
Dunedin, New Zealand
November 20-November 23
ISBN: 0-8186-7174-2
Max Bailey, University of Otago
Nikola Kasabov, University of Otago
Peter Mason, University of Otago
Andrew Gray, University of Otago
Tico Cohen, Waste Solution Ltd
This paper provides a brief introduction to our experiences and results of applying artificial intelligence techniques to the real world problem of predicting inflow to a Sewage Treatment Plant. The basic structure of the plant is described followed by a discussion of how recurrent neural networks may be applied to the problem of predicting systems with diurnal and chaotic components. Next, the software system developed and implemented on the site is presented. A brief discussion on the feasibility of incorporating the prediction module within a hybrid system environment follows. Finally, the possibility of using fuzzy logic for control in similar problems is discussed with reference to some preliminary experiments.
Index Terms:
Neural networks, prediction, industry, engineering, chaos, chaotic, time series, hybrid systems, FuzzyCOPE
Citation:
Max Bailey, Nikola Kasabov, Peter Mason, Andrew Gray, Tico Cohen, "Hybrid Systems for Prediction - A Case Study of Predicting Effluent Flow to a Sewage Plant," annes, pp.261, 2nd New Zealand Two-Stream International Conference on Artificial Neural Networks and Expert Systems (ANNES '95), 1995
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