DocumentCode :
1661485
Title :
Hybrid systems for prediction-a case study of predicting effluent flow to a sewage plant
Author :
Bailey, Max ; Kasabov, Nilkola ; Cohen, Tico ; Mason, Peter ; Gray, Andrew
Author_Institution :
Dept. of Inf. Sci., Otago Univ., Dunedin, New Zealand
fYear :
1995
Firstpage :
261
Lastpage :
264
Abstract :
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
Keywords :
civil engineering computing; fuzzy control; fuzzy logic; learning (artificial intelligence); recurrent neural nets; waste disposal; artificial intelligence; case study; chaotic components; diurnal components; effluent flow prediction; fuzzy control; fuzzy logic; hybrid systems; prediction module; recurrent neural networks; sewage treatment plant; Artificial intelligence; Buffer storage; Chaos; Computer aided software engineering; Effluents; Fuzzy logic; Information science; Neural networks; Sewage treatment; Statistical analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Neural Networks and Expert Systems, 1995. Proceedings., Second New Zealand International Two-Stream Conference on
Conference_Location :
Dunedin
Print_ISBN :
0-8186-7174-2
Type :
conf
DOI :
10.1109/ANNES.1995.499485
Filename :
499485
Link To Document :
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