Prediction and optimization of runoff via ANFIS and GA

D. K. Ghose, S. S. Panda, P. C. Swain

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

In planning of water resource projects, the estimation of the availability of water plays an important role. The first step in the water availability estimation is the computation of runoff resulting from the precipitation on river catchments. The length of the runoff measured in a stream may be of short period or long period depending upon the catchment characteristics. Keeping this in mind the present work is focused on two different model generation. In the first phase of this study, runoff rating curves are developed considering present day water level (H(t)) as input and present day runoff (Q(t)) as the model output. In the second phase of the study runoff prediction models are developed considering 1 day lag water level (H(t - 1)), 2 day lag water level (H(t - 2)) and 1 day lag runoff (Q(t - 1)) as inputs and 1 day ahead runoff (Q(t + 1)) as the output of the model. Models developed and used for prediction of runoff are Non-Linear Multiple Regression (NLMR) and Adaptive Neuro-Fuzzy Inference System (ANFIS). Both the models were trained and tested to predict the performance of models. Genetic Algorithm (GA) is then coupled with NLMR model to obtain the condition of hydrological parameter for which the runoff is maximum.

Original languageEnglish (US)
Pages (from-to)209-220
Number of pages12
JournalAEJ - Alexandria Engineering Journal
Volume52
Issue number2
DOIs
StatePublished - Jun 2013

Fingerprint

Fuzzy inference
Runoff
Genetic algorithms
Water levels
Catchments
Availability
Water resources
Water
Rivers
Planning

Keywords

  • ANFIS
  • GA
  • NMLR
  • Runoff

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Prediction and optimization of runoff via ANFIS and GA. / Ghose, D. K.; Panda, S. S.; Swain, P. C.

In: AEJ - Alexandria Engineering Journal, Vol. 52, No. 2, 06.2013, p. 209-220.

Research output: Contribution to journalArticle

Ghose, D. K. ; Panda, S. S. ; Swain, P. C. / Prediction and optimization of runoff via ANFIS and GA. In: AEJ - Alexandria Engineering Journal. 2013 ; Vol. 52, No. 2. pp. 209-220.
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