Kohonen self-organizing map for multiple-outlet sluice gates control system

Author

Li, Zhongzhi

Author_Institution

Dept. of Network Eng., Chengdu Univ. of Inf. Technol., Chengdu, China

Volume

1

fYear

2010

fDate

10-12 Aug. 2010

Firstpage

353

Lastpage

356

Abstract

In multiple-outlet sluice gates control systems, the open-close state of each sluice gate is usually decided by personal experience based on upstream water height and downstream water height. In this paper, a new method is proposed to determine the state of multiple-outlet sluice gates. Using Kohonen self-organizing map neural network, the proposed method maps the expectation-running water heights into the sluice gates state. From the experimental results, the method can get effective multiple-outlet sluice gates features by mapping a continuous input vector into a discrete output vector.

Keywords

hydraulic systems; self-organising feature maps; Kohonen self-organizing map neural network; continuous input vector; discrete output vector; expectation-running water heights; multiple-outlet sluice gates control system; Artificial neural networks; Conferences; Control systems; Joints; Logic gates; Neurons; Organizing; feature mapping; multiple-outlet sluice gates control system; neural network; self-organizing map;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2010 Sixth International Conference on

Conference_Location

Yantai, Shandong

Print_ISBN

978-1-4244-5958-2

Type

conf

DOI

10.1109/ICNC.2010.5583840

Filename

5583840