Application of Artificial Neural Network to the Assessment Environmental Quality of Urban Wetland in Northeast China

Abstract:

North shore of Songhua river is the major development zone in carrying out the program of enlarging urban areas along river regions in Harbin. In this paper, the authors regard urban wetland of Harbin in north shore of Songhua river as the research object, B-P artificial neural network is applied to build the assessment model of the eco-environmental quality. The authors take 6 factors for samples to be evaluated, the well –trained network is used to assess eco-environmental quality, The overall evaluation result being indicates that overall ecological environment mass of wetland in north shore of Songhua river is with difficulty qualified (0.6116), and by investigation and analysis, it turns out that the assessing results accord well with the actual situation, and provides the theory basis for the urban wetland healthy development. At the same time, applying artificial neural network model to wetland ecological environment quality evaluation, specifically for different ecosystem increasing network secret node or lays numbers come rise neural networks learning ability and train effect.

• Periodical: Advanced Materials Research (Volumes 518-523)
• Pages: 1455-1458
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.518-523.1455
• Online since: May 2012
• Authors: Ji Guang Li, Yi Bin Ren, Qi Shuo Wang, Shuang Qi Tian, Ji Wei He, He Wang, Xian Guo Lu, Nan Qi Ren
• Keywords: Artificial Neural Network (ANN), Environment Quality, Urban Wetland

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DOI: 10.1016/s0309-1708(02)00094-5

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