Developing a conjunctive nonlinear model for inflow prediction using wavelet transforms and artificial neural networks: A case study of Dez reservoir dam, Iran

Mehdikhani, H ; Sharif University of Technology | 2006

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  1. Type of Document: Article
  2. DOI: 10.1061/40875(212)7
  3. Publisher: 2006
  4. Abstract:
  5. Dez reservoir dam is one of the famous dams in Khuzestan province in southwestern part of Iran. Operation of Dez reservoir dam and it's strategic position has an important role regard to providing country's net power, it's long precedence in operation, Dam dimension, multidisciplinary uses and existence of essential land use in downstream. Thus inflow forecasting could have a great role in effective operation of dam, flood non-structural and risk management by applying an effective flood warning. The more accurate the forecasting of inflow to reservoir will be results the less peak outflow and less risk to downstream. This paper presents a new Conjunctive nonlinear model using Wavelet transforms and Artificial Neural Network. It plays an important role in improving the accuracy of 15-day and monthly prediction inflow time series. Calibration and verification of wavelet network model for prediction of inflow to Dez reservoir as the case study have shown that the method is applicable. For the particular case of the Dez reservoir, the overall forecast accuracy of the conjunction model, as measured by R2, RMSE (Root Mean Square Error) and NMSE (Normal Mean Square Error) was better than conventional ANN prediction model. Copyright ASCE 2006
  6. Keywords:
  7. Conjunctive nonlinear model ; Inflow forecasting ; Inflow time series ; Wavelet network model ; Mathematical models ; Nonlinear systems ; Product development ; Reservoirs (water) ; Risk management ; Wavelet transforms ; Neural networks
  8. Source: Operations Management 2006, Sacramento, CA, 14 August 2006 through 16 August 2006 ; Volume 2006 , 2006 , Pages 69-78 ; 0784408750 (ISBN); 9780784408759 (ISBN)
  9. URL: https://ascelibrary.org/doi/10.1061/40875%28212%297