Research on river water quality evaluation based on the GA-PP and improved fuzzy model

Abstract

To ensure the water quality of rivers, it is crucial to scientifically evaluate their water quality status. This study takes a river in Jiangsu, China, as an example to establish six targeted main indicators for river water quality evaluation and uses a projection pursuit model optimized by the genetic algorithm to determine weights. Applying the improved fuzzy evaluation model to the final evaluation of water quality, the results indicate that this article adopts a weight calculation model that reduces dimensionality without losing data features, and the comprehensive evaluation model is also more complete, resulting in more accurate evaluation results. According to model analysis, the summer water quality is good and peaks from June to July. This article proposes corresponding measures and suggestions in response to the reasons behind this seasonal change. The evaluation model used in this article is superior to other models in terms of accuracy and portability, making it an excellent choice for river water quality evaluation. It can provide valuable technical guidance for similar river water quality evaluations. HIGHLIGHTS In the evaluation of river water quality, the high-dimensional data dimensionality reduction operation optimized by the genetic algorithm projection pursuit (GA-PP) is not easy to lose the original features of the data and is quite suitable for calculating weights.; The improved fuzzy evaluation model is also superior to the traditional fuzzy comprehensive model and can more comprehensively evaluate water quality data.;

Keywords

• improve fuzzy evaluation model
• projection pursuit
• river water quality