An estimation of runoff ratio by using artificial neural network with radar echo data

Author

Suzuki, S. ; Mizuno, K. ; Yukita, K. ; Goto, Y. ; Ichiyanagi, K. ; Matsumura, T.

Author_Institution

Aichi Inst. of Technol., Toyota, Japan

Volume

3

fYear

2002

fDate

6-10 Oct. 2002

Firstpage

2273

Abstract

This paper describes an application of a neural network for estimating the runoff ratio from radar echo data. A neural network system is developed through a case study on a dam for hydro-power plant located the upper district of the Yahagi River in Central Japan. The authors use the two types of neural networks; one of the types is for estimating the ground rainfall distribution from radar echo data and another one is for estimating the runoff ratio from estimated ground rainfall. It is found from their investigations that estimating accuracy of the runoff ratio is improved by utilization the radar echo data.

Keywords

geophysics computing; groundwater; hydroelectric power; hydroelectric power stations; neural nets; power generation planning; rain; Japan; Yahagi River; artificial neural network; estimating accuracy; ground rainfall; ground rainfall distribution; hydropower plant dam; radar echo data; runoff ratio estimation; Artificial neural networks; Equations; Meteorological radar; Neural networks; Radar applications; Rain; Read only memory; Reservoirs; Rivers; Water resources;

fLanguage

English

Publisher

ieee

Conference_Titel

Transmission and Distribution Conference and Exhibition 2002: Asia Pacific. IEEE/PES

Print_ISBN

0-7803-7525-4

Type

conf

DOI

10.1109/TDC.2002.1177818

Filename

1177818