Entropy-cloud model of heavy metals pollution assessment in farmland soils of mining areas

Abstract

An entropy-cloud model is proposed to deal with soil heavy metal pollution assessment based on entropy and cloud model theory. Parameters of the cloud model of each heavy metal level are calculated with the chosen indicators, and hybrid entropy weights are determined based on Shannon entropy and the analytic hierarchy process (AHP) to generate an entropy-cloud model of all indicators. Certainty degrees of each level are calculated by the entropy-cloud model, and the fuzzy entropy of certainty degrees is calculated to indicate the complexity of heavy metal pollution. Heavy metal pollution of 10 farmland soils in mining areas is assessed by the entropy-cloud model. Comparative studies with variable fuzzy sets, artificial neural network, and normal cloud model show that the entropy-cloud model is effective and intuitive, which can assess the soil heavy metal pollution from two aspects of level and complexity. Different from other methods, this model provides a new way to assess soil heavy metal pollution.