This project belongs to the field of computer decision support systems.
Water environment protection is not only related to economic development, but also closely related to the health and life safety of the people. However, with the continuous growth of population, the rapid development of industrial and agricultural production, and the frequent occurrence of water transportation accidents, water environment security is under increasingly serious threat. In order to promptly and accurately grasp the situation of water pollution incidents, control the development of events, reduce losses, analyze the causes of accidents, and reduce the occurrence of water pollution incidents, there is an urgent need to effectively monitor the water environment. Strengthening the protection of the water environment and building a network system for automatic water quality monitoring and intelligent prediction and early warning are of great significance to people's health, economic construction and social stability.
This project focuses on the current difficulties in automatic water pollution monitoring and intelligent prediction and early warning systems: timely and accurate prediction and early warning of regional water quality conditions before water pollution emergencies occur, and accurate evaluation of regional water quality conditions through data collected by various water quality monitoring equipment. Regional water quality conditions, effective identification of water quality monitoring sensor failures and sudden water pollution incidents, etc., carried out theoretical research and technological innovation, and achieved the following innovative results:

1. A dynamic prediction and early warning method for water quality in areas closely related to water bodies is proposed, and a multi-agent sewage treatment decision support system based on enhanced learning, a pollution source discharge process monitor, and an online monitoring and analysis system for pollution source discharge (process) conditions are designed and developed. Early warning before pollutants reach sensitive areas in water areas is conducive to suppressing the degree of water pollution disasters, slowing down the spread time, and reasonably controlling and rectifying water pollution incidents. This method not only is the evaluation results relatively objective and accurate, does not require precise mathematical models to carry out complex calculations, and can dynamically evaluate the water quality in the same area over a period of time, but also can use known monitoring data from a monitoring point to evaluate the water quality of areas closely related to water bodies. Conduct prediction and early warning of water quality conditions.
2. Propose a biological water quality evaluation method and a multi-indicator comprehensive evaluation method based on the relationship between aquatic organisms and water quality, and design and develop a water quality pollution monitoring network system, a pollution source monitoring information system and an operation and maintenance management platform. The biological water quality evaluation method accurately grasps the water quality status of the area by analyzing the aerobic requirements of benthos appearing in the monitored waters; the multi-indicator comprehensive evaluation method of water quality adopts a comprehensive weight based on game theory based on a combination of the G1 method and the entropy method., overcomes the one-sidedness of the single factor method, improves the accuracy of weight determination, makes the determination of the comprehensive coefficient more in line with the actual situation, and solves the problems of information loss in traditional composite algorithms and the tendency to equalize evaluation results.
3. Propose a fault diagnosis method for automatic water quality monitoring sensors under complex circumstances such as sudden pollution incidents are prone to occur, and design and develop a mother-child environmental protection data collection and transmission instrument and software, and environmental data collection and control system software. The method has high modeling and analysis efficiency, and can monitor the working status of water quality monitoring sensors in real time. It can effectively identify sudden water pollution incidents and sensor faults, discover sensor faults in time, improve the efficiency and accuracy of identification, and also improve the accuracy of water quality data. Accuracy and convenience of sensor maintenance.
   The project results have obtained 1 authorized invention patent, 2 utility model patents, and 7 registered software copyrights; 1 monograph has been published and more than 20 papers have been published, including 11 SCI/EI searches. Related technologies and products have been applied to more than 300 water supply, chemical, electronics, textile enterprises and environmental protection management departments in Jiangsu, Anhui and other places. Automatic monitoring is used to timely and accurately grasp the actual conditions of drinking water, pollution sources, and sewage discharge, and through intelligent prediction Early warning grasps the changing trend of the water environment, effectively suppresses the spread of pollution and prevents the occurrence of water pollution incidents, and contributes to water environment protection. From January 2013 to December 2015, The new output value of this project is 42.3 million yuan. According to incomplete statistics, the indirect economic benefits exceed 120 million yuan.