Application of the neural network in prediction for chlorophyll-a in branch backwater region

Key words: 
• branch /
• backwater region /
• chlorophyll-a /
• neural network /
• principal component analysis

Abstract: Taking Linjiang river which is a branch of Yangtze River as research object to evaluate the feasibility of neural network model for simulating chlorophyll-a trend in branch backwater region. By using the method of principal component analysis (PCA) to select the main indexes which affect the chlorophyll-a trend, the RBF neural network model was created based on the database of indexes. The training and testing results of model indicated that the simulating accuracy of model was high; it showed that the RBF neural network model could be used for simulating the chlorophyll-a short-term trend in branch backwater region. By analyzing the influencing factors of chlorophyll-a in Linjiang river backwater region, the result showed that controlling phosphorus content would be important to prevent and control Linjiang river backwater region’s eutrophication.