Intelligent diagnosis method for river and lake ecosystem health based on improved slime mold algorithm-optimized SVR.

ABSTRACT: In the diagnosis of river and lake ecosystems, there are complex nonlinear relationships among water quality parameters, and their dynamic change mechanisms are rather complicated. Traditional statistical analysis methods have limitations in providing precise assessment and timely early warning. To address the bottlenecks of traditional methods in accuracy, timeliness, and applicability, an intelligent diagnostic model based on improved slime mold algorithm-optimized support vector regression is proposed. This model improves its parameter optimization ability through dynamic weight strategy and adaptive search mechanism, and combines LightGBM feature selection to construct a combined model, effectively solving the problems of high-dimensional data modeling and dynamic adaptability. The exp

SUBMITTER: Chi R 

PROVIDER: S-EPMC12823004 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature