Study On Black-Stink Assessment Based On BP Nerual Network And Fuzzy Mathematics Of FenRiver In Taiyuan City

Urban rivers are an important component of urban water environment and an indispensable resource of the formation and development of the city. But with the economic development and the increasing urban population, the discharging amounts of industrial wastewater and domestic sewage increased ceaselessly.The lag of the Municipal construction made large quantity of waste and polluted water has not been effectively dealt and rowed to the inside or around the city's rivers, causing serious pollution to water bodies of rivers and serious black-stink to many river sections. Aquatic animals and plants have almost disappeared, the river lost its original function. The city's sustainable development has been restricted. While the black-stink effective and objective assessments of water bodies are foundation and key of water pollution prevention and management decision-making, so the study on black-stink evaluation of urban rivers has important significance.This paper takes the Fen River in Taiyuan city as the research object, it has carried on a detailed understanding the tributaries of the river and the data of the sewage outfall;it has set up to monitor cross-section based on the monitoring fabric-point principle; Using high-frequency sampling of the river water quality had long-term monitoring. It takes the material of actual water quality as a base, exploring the combination of the fuzzy and the neural network to establish the evaluation model of BP network membership of a black-stink water quality. Using this model evaluated to the Fen River black-stink in Taiyuan city and the model with the validation measured data is suited for the actual situation of Fen River in Taiyuan city and it provides a basis for effective governance of urban rivers.The results of the research mainly in the following three aspects:(1)By collecting the datum of tributaries and the drains of river and setting the monitoring cross-section according to the river's natural structure and distribution of the sewage outfall, the long-term monitor to the water quality is carried out and analyzed in the laboratory.(2)On the basis of monitoring data, it carries out river water quality assessment. By applying of a single pollution index, it obtains the exceeded project of the monitoring section and single-factor exceeding rate; By applying of the method of pollution load ratio, it analyses main polluting factors of river, gives the weight of various pollutants and all tributaries of the contribution rate of pollution.(3)Through the literature reading and the conjunction with the actual situation of Taiyuan, it analyses the impact of monitoring projects on black and stink, and screens to determine major impact factor on black-stink Fen River in Taiyuan. For the role of black-odor the river is the result of multiple factors, combined with the ambiguity of existence of the water quality characteristics of classification, the black-stink water quality evaluation model of the BP neural network subordinate degree is established by the combination of neural networks and fuzzy.By applying of matlab technology procedures, it establishes a suitable black and stink evaluation model of the Fen River in Taiyuan city. According to the established black-stink evaluation model, it puts forward the assessment of the black and stink's degree of the Fen River in Taiyuan city and quantitatively reflects the black and stink's degree of river. and analyses the time variation rules and spatial distribution of the Fen River in Taiyuan city. and river models can reflect the actual situation on the black section of Fen River in Taiyuan City and correct evaluation of the extent stinky. Then analyzed the causes of black-odor rivers in Taiyuan and made the governance program.