DocumentCode
2455760
Title
Study on the salinity modeling based on back-propagation neural network
Author
Gao, Guodong ; Zhang, Wenxiao ; Mu, Guangyu
Author_Institution
Coll. of Mech. Eng., Dalian Ocean Univ., Dalian, China
fYear
2011
fDate
24-26 June 2011
Firstpage
3592
Lastpage
3594
Abstract
A new BP neural network is introduced and at the same time, its´ structure, feature and principium are also expatiated. In order to approach compensate the effects of improves non-linearity, a BP neural network model is set up and trained in this paper. The test result indicates that: this method is practical and dependable in the field of salinity modeling, has a good applied foreground.
Keywords
agriculture; backpropagation; neural nets; BP neural network model; agriculture; back-propagation neural network; salinity control; salinity measurement; salinity modeling; Adaptation models; Analytical models; Artificial neural networks; Biological system modeling; Learning systems; Mathematical model; Training; BP neural network; forecast; math modeling; salinity; simulation;
fLanguage
English
Publisher
ieee
Conference_Titel
Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-9172-8
Type
conf
DOI
10.1109/RSETE.2011.5965104
Filename
5965104
Link To Document