Efficiency assessment of local prediction method considering reconstruction of phase space and artificial neural network model for prediction of runoff (Case Study: Pole-kohneh Station, Kermanshah)

Zounemat-Kermani, Mohammad; Amirkhani, Khatereh

doi:10.22067/civil.v28i2.41135

Efficiency assessment of local prediction method considering reconstruction of phase space and artificial neural network model for prediction of runoff (Case Study: Pole-kohneh Station, Kermanshah)

Document Type : پژوهشی

Authors

Mohammad Zounemat-Kermani ¹

Khatereh Amirkhani ²

¹ Shahid Bahonar university of Kerman

² Shahid Bahonar University of Kerman

10.22067/civil.v28i2.41135

Abstract

In this research prediction methods of artificial neural network and chaos theory are employed to predict daily, weekly and monthly runoff. For this, runoff series data observed at Pole-Kohneh located in the Qareh-Soo River. The nonlinear predictions of chaos are found to be in close agreement with the observed runoff, with high correlation coefficient for daily and weekly time scales. Predicted results of monthly time scale are not satisfying which indicating the chaos behavior in daily and weekly scales. The predicted results of ANN are inferior to chaos for daily and weekly scales but superior to chaos for monthly scale.

Keywords

Runoff time series

Chaos Theory

local prediction method

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