Unascertained measure assessment on environmental impact of tailings pond

This The index system of environmental impact assessment of tailings pond is hierarchal structure. As there is inherent uncertainty in determining the evaluation grade of low-level indicators and the relationship between the up-level and low-level indicators is non-linear, therefore, the evaluation model should have to deal with the uncertainty of information and achieve the non-linear conversion. As we can describe the uncertainty of the evaluation grade of low-level indicators with membership function, the fuzzy model is chosen to be the best model for environmental impact assessment. However, for the existing fuzzy evaluation model, the algorithm for the “non-linear conversion” of membership between the up-level indicators and low-level indicators is not correct. Therefore, firstly, we construct a learning algorithm based on the divisional right filter by mining the information hidden in the membership degree space, and achieve the “non-linear conversion” of membership degree. Secondly, we establish the calculation model for environmental impact assessment of tailings pond, and at last we illustrate the application of the model with one example.