2026-10-11T21:05:11Z https://www.scidb.cn/oai

10.57760/sciencedb.iga.001gc 2026-09-18T15:16:48Z

2026-09-18 XDA28010501 Dataset on the Migration and Transformation Process of Soil Herbicides and the Dynamic Changes at Multi-media Interfaces (New) doi:10.57760/sciencedb.iga.001gc en This dataset is mainly used for constructing and evaluating prediction models for the typical degradation rates of herbicides in the soil environment. The constructed models belong to typical nonlinear data-driven models. Their basic principle is to learn from the existing sample data to establish a complex nonlinear mapping relationship between the input environmental factors and the target variable (degradation rate of the herbicide), thereby achieving the prediction of the degradation rate under unknown conditions. Different from traditional mechanism models that rely on explicit physical and chemical process equations, this method reveals the potential statistical patterns among variables through data mining, thus having obvious advantages in handling systems with multiple factors coupling, complex or unclear mechanism relationships. Herbicide dissipation rate pre; Machine learning models; Soil physicochemical propertie 高娟 PUBLIC https://creativecommons.org/licenses/by-nc/4.0/ dataset Science Data Bank