Pre-selected water quality monitoring network multi-objective optimized deployment method for some monitoring points

Abstract

The present invention discloses a pre-selected water quality monitoring network multi-objective optimized deployment method for some monitoring points. The method comprises the following steps: selecting all candidate monitoring points according to the water area of the monitoring area; performing hydraulic modeling and simulating water pollution incidents at any candidate monitoring point in themonitoring area; determining an optimization objective function, and pre-selecting monitoring points according to monitoring requirements and expert experience; and calculating the average pollution monitoring time and the successful monitoring probability according to the cost function, and updating the pbest and gbest sets, ensuring that the preselected some monitoring points are included in thesolution set, and finally finding the Pareto front as the optimal solution set including the preselected monitoring points. The method disclosed by the present invention is applied to the optimized deployment of the water quality monitoring system under the condition that certain monitoring points have been determined, and optimization can be performed according to different objectives, so that the detection time is the least, the detection reliability is the highest, and the graph center is the best.

Description

technical field [0001] The invention relates to an optimal deployment method, in particular to a multi-objective optimal deployment method for a water quality monitoring network with some monitoring points preselected. Background technique [0002] In recent years, affected by various factors such as the rapid development of industrial production and population increase, the deterioration of the water environment has intensified and water pollution incidents have occurred frequently, posing a serious threat to economic development and social stability, which has attracted widespread attention at home and abroad. Monitoring the water environment closely related to human life can grasp the distribution of water pollutants, ascertain various pollutants, trace the source, route, migration and transformation of pollutants, and the law of growth and decline, predict the trend of water pollution changes, and provide a basis for the evaluation of water environment quality. And take ...

AI Technical Summary

Problems solved by technology

However, the traditional multi-objective optimization algorithm aims to obtain the global optimal solution, which cannot meet this actual management requirement, so it cannot be well applied to the optimal deployment of the water quality monitoring system when some monitoring points are pre-selected.

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