Research on Water Quality Monitoring Section Optimization Based on Multi-agent Model

Abstract

In order to conduct reasonable and effective water quality (WQ) section monitoring of lakes, water reservoirs, and rivers this paper presents a multiagent model to optimize the WQ monitoring sections. First, the paper establishes a normalized matrix based on the original WQ monitoring data and from the data extracted principal/nonprincipal components as effective WQ features. Then, multi-WQ-agents model is built including comprehensive evaluation scores (CES) of principal/nonprincipal components in each WQ-agent and interaction rules of WQ-agents on the basis of the multiagent theory, in which the adjacent WQ-agents can be merged or split according to the similarity of CES. Therefore, the research realizes merge in the coarse segmentation of all WQ-agents, called as Agent ^#. On the condition that the number of Agent ^#s is smaller than the predefined threshold, the Agent ^#s would be spilt further in the fine segmentation, called as Agent*s. Finally, the central points of Agent* are selected as the measuring samples of WQ monitoring sections. The result shows that multiagent model can improve the monitoring quality, cut cost, and provides a creative measure of WQ monitoring section optimization.