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Entropy-Cloud Model of Heavy Metals Pollution Assessment in Farmland Soils of Mining Areas

机译:矿区农田土壤重金属污染评价的熵云模型

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摘要

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.
机译:提出了一种基于熵和云模型理论的熵云模型,用于土壤重金属污染评价。使用所选指标计算每个重金属水平云模型的参数,并基于香农熵和层次分析法(AHP)确定混合熵权,以生成所有指标的熵云模型。通过熵-云模型计算出每个水平的确定度,并通过计算确定度的模糊熵来表示重金属污染的复杂性。利用熵云模型对矿区10种农田土壤的重金属污染进行了评价。通过对可变模糊集,人工神经网络和正常云模型的比较研究表明,熵云模型是有效和直观的,可以从层次和复杂度两个方面对土壤重金属污染进行评价。与其他方法不同,该模型提供了一种评估土壤重金属污染的新方法。

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