Abstract
In view of the strong nonlinearity of the resource investment and evaluation level of Energy-saving and Emission-reduction (ESER) in coal mine, this paper firstly established the input index system, then established a mechanism model of ESER resources and ESER level based on SVR, used genetic algorithm (GA) to optimize the parameters of the SVR model, and introduced the Cross-validation to improve the process for the best SVR model. The performance of the improved model is measured against particle swarm optimization algorithm. The results showed that: the model using improved GA-SVR fitted better with the nonlinear relationship between ESER resources and ESER level, and this model also had a stronger effectiveness and generalization ability.
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Wang, Jf., Chen, Z., Feng, Lj., Zhai, Xq. (2016). A Mechanism Model of Resource Investment and Evaluation Level of Energy-Saving and Emission-Reduction in Coal Mine. In: Qi, E., Shen, J., Dou, R. (eds) Proceedings of the 22nd International Conference on Industrial Engineering and Engineering Management 2015. Atlantis Press, Paris. https://doi.org/10.2991/978-94-6239-180-2_48
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DOI: https://doi.org/10.2991/978-94-6239-180-2_48
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