Neural Network Using to Analyze the Results of Environmental Monitoring of Water

V. Usachev, L. Voronova, V. Voronov, I. Zharov, Vladimir G. Strelnikov
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引用次数: 12

Abstract

The acuteness of the environmental tracking problem is constantly growing. Currently, environmental issues are analyzed using big data. Many open data sources (Kaggle, Open Data Portal of the Russian Federation, etc.) contain a variety of environmental information. Based on the data and using the tools for analyzing big data and machine learning, a system has been developed that simulates the state of water quality in the Moscow waters. On the basis of the indicators obtained, the neural network was trained, which classifies the state of the reservoir into good and deviant.
应用神经网络分析水体环境监测结果
环境跟踪问题的尖锐性日益突出。目前,环境问题是用大数据来分析的。许多开放数据源(Kaggle、俄罗斯联邦开放数据门户等)包含各种环境信息。基于这些数据,并使用分析大数据和机器学习的工具,开发了一个模拟莫斯科水域水质状况的系统。在此基础上对神经网络进行训练,将储层状态分为良好状态和异常状态。
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