Lowland Technology International
Vol 4 No 2, Dec (2002)

APPLICATION OF ANN FOR RESERVOIR INFLOW FORECASTING USING SNOWMELT EQUIVALENT IN THE KARAJ RIVER WATERSHED

H. R. Eslami (Unknown)
K. Mohammadi (Unknown)



Article Info

Publish Date
06 Dec 2002

Abstract

Three different methods were used to predict the spring inflow into the Amir Kabir reservoir, which is located near Tehran, Iran. The spring inflow accounts for almost 60 percent of annual inflow to the reservoir. Utilizing the results of an artificial neural network (ANN) model, the inflow to Amir Kabir reservoir is predicted. It will be compared with two other methods: ARIMA time series and regression analysis between some hydroclimatological data and inflow. Using the thirty years of observed data proved that the ANN has a better performance than that the other methods have.

Copyrights © 2002






Journal Info

Abbrev

ialt_lti

Publisher

Subject

Civil Engineering, Building, Construction & Architecture Engineering Transportation

Description

The Lowland Technology International Journal presents activity and research developments in Geotechnical Engineering, Water Resources Engineering, Structural Engineering, Transportation Engineering, Urban Planning, Coastal Engineering, Disaster Prevention and Mitigation ...