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On Evaluation Model of Circular Economy for Iron and Steel Enterprise Based on Support Vector Machines with Heuristic Algorithm for Tuning Hyper-parameters |
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PP: 2215-2223 |
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Author(s) |
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Zhifang Zhou,
Xiaohong Chen,
Xu Xiao,
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Abstract |
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| With more severe resource scarcity and environmental problems, the evaluation of circular economy in microcosmic level
has become the focus of the academic world. Based on the concept of circular economy, this paper not only structures the evaluation
index system of circular economy for iron and steel enterprises, builds the evaluation model of circular economy for iron and steel
enterprises based on Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel, but achieves the optimization of
kernel function parameters, penalty factors and insensitive parameters based on a heuristic algorithm for tuning hyper-parameters.
Furthermore, the evaluation model is tested for circular economy evaluation in the major iron and steel enterprises in China. The
research demonstrates that the evaluation results of heuristic algorithm with SVM are more accurate, and this model is more suitable
for iron and steel enterprises to evaluate circular economy, compared with the evaluation method of BP neural network. |
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