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Evaluation of Water Quality for Mangrove Ecosystem Using Artificial Neural Networks

机译:人工神经网络在红树林生态系统水质评价中的应用

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With the rapid urbanization and socioeconomic development, mangrove ecosystem, especially the water quality in the coastal environment is getting increasingly vulnerable. In our work, the model of back-propagation (BP) neural network was established based on the national standards of surface water (GB3838-2002). The resulting model was used to classify water quality of mangrove. Then the relationship between water quality and diseases and insect pests was analyzed. The results show that water quality of 1, 2 and 3 monitoring sites is the worst, and the water quality in August is significantly better than that in the other two months, which would be useful for recognizing the polluted areas and determining the priority preservation areas. Additionally, it is found that there is relevance between water quality and diseases and insect pests, which could provide basis for subsequent study on diseases and insect pests.
机译:随着快速的城市化和社会经济发展,红树林生态系统,特别是沿海环境中的水质日益脆弱。在我们的工作中,根据国家地表水标准(GB3838-2002)建立了反向传播(BP)神经网络模型。所得模型用于对红树林水质进行分类。然后分析了水质与病虫害之间的关系。结果表明,1、2、3个监测点的水质最差,8月的水质明显好于其他两个月,这对于识别污染区和确定优先保护区很有帮助。 。另外,还发现水质与病虫害之间存在相关性,这可以为以后对病虫害的研究提供依据。

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