• 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