Embedded water quality field analyzer based on neural network

Author

Xueliang, Zhao ; Yun, Shi ; Xiaohui, Wang ; Lei, Zhang

Author_Institution

Center For Hydrogeology & Environ. Geol., CGS, Baoding, China

Volume

2

fYear

2009

fDate

5-6 Dec. 2009

Firstpage

27

Lastpage

29

Abstract

Taking a water quality field analyzer as an example, a solution is proposed based on embedded and neural network. The hardware and the software design are introduced in detail. Then we sum up the complex nonlinear relation between the evaluation standard and the evaluation results through the continual study and training of BP neural network, and finally establish the BP neural network model. The system has wide application prospect with the advantages of small volume, low cost, high reliability, etc.

Keywords

Linux; backpropagation; embedded systems; environmental science computing; learning (artificial intelligence); microcomputers; neural nets; water quality; backpropagation neural network; complex nonlinear relation; embedded system; evaluation results; evaluation standard; water quality field analyzer; Computer displays; Electronic mail; Hardware; Linux; Neural networks; Operating systems; Sensor systems; Switches; Temperature sensors; Water resources; ARM; Linux operating system; neural network; water quality;

fLanguage

English

Publisher

ieee

Conference_Titel

Test and Measurement, 2009. ICTM '09. International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-4699-5

Type

conf

DOI

10.1109/ICTM.2009.5413057

Filename

5413057