Abstract
To objectively evaluate the resource efficiency and environmental impact of iron and steel enterprises, it is necessary to comprehensively evaluate the greenness of their manufacturing process. In this paper, based on the green evaluation index of iron and steel enterprises, a two-level green evaluation system derived from the manufacturing process is established, and a green evaluation and prediction model of the manufacturing process are established. Firstly, the data in the actual production process of iron and steel enterprises are normalized. The first 75% of the data is taken as the training set, and the last 25% as the test set. Then, the data set is imported into the constructed BP neural network for training. Finally, through the analysis of the training results, it can simulate the experts to evaluate the diagnosis and predict the optimized manufacturing process.
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This work is financially supported by National Natural Science Foundation of China (Grant No. 51775392).
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Xiao, J., Zhao, G., Yan, P. (2021). Research on Quantitative Evaluation of Green Property of Iron and Steel Enterprises Based on BP Neural Network. In: Scholz, S.G., Howlett, R.J., Setchi, R. (eds) Sustainable Design and Manufacturing 2020. Smart Innovation, Systems and Technologies, vol 200. Springer, Singapore. https://doi.org/10.1007/978-981-15-8131-1_44
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DOI: https://doi.org/10.1007/978-981-15-8131-1_44
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