Title :
Content prediction of Chlorophyll-a in seawater based on Fuzzy BP method
Author :
Ying Zhang ; Caijuan Li ; Xiaohua Hu
Author_Institution :
Coll. of Inf. Eng., Shanghai Maritime Univ., Shanghai, China
Abstract :
Chlorophyll-a is an important index of water quality for seawater, which can indicate the state of algae reproduction, further more it can predict the disaster of red tide by prediction model. The content of Chlorophyll-a of seawater is affected by many physical-chemical factors, this complex relationship among them is difficult to be described by ordinary mechanism expression. In this paper, we use Fuzzy BP model to describe this complex nonlinear system, and give a dynamic estimate to the output variables of the system. The PCA(Principal Component Analysis) method had been used to reduce the dimension of the sample data, simplify the complexity of the model system, this measure can make the model has a faster convergence rate and a relative low dimension. The experiment illustrates that fuzzy BP model based on PCA method can give the prediction for the content of chlorophyll-a in seawater to some degrees.
Keywords :
backpropagation; environmental science computing; fuzzy set theory; geophysics computing; neural nets; oceanographic techniques; principal component analysis; seawater; water quality; Chlorophyll-a content prediction; PCA method; algae reproduction; complex nonlinear system; fuzzy BP method; ordinary mechanism expression; physical-chemical factors; principal component analysis; seawater; water quality; Algae; Biological system modeling; Input variables; Predictive models; Principal component analysis; Sea measurements; Training; chlorophyll-a; fuzzy BP network; principal component analysis (PCA); state prediction;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-180-9
DOI :
10.1109/FSKD.2011.6019495