Calorific Value Forecasting of Coal Gangue with Hybrid Kernel Function–Support Vector Regression and Genetic Algorithm

Xiangbing Gao, Bo Jia, Gen Li and Xiaojing Ma
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Xiangbing Gao: Xinjiang Xinneng Group Company Limited, Urumqi Electric Power Construction and Commissioning Institute, Urumqi 830000, China
Bo Jia: State Grid XinJiang Company Limited Electric Power Research Institute, Urumqi 830000, China
Gen Li: School of Electrical Power Engineering, South China University of Technology, Guangzhou 510641, China
Xiaojing Ma: School of Electrical Engineering, Xinjiang University, Urumqi 830017, China

Energies, 2022, vol. 15, issue 18, 1-15

Abstract: The calorific value of coal gangue is a critical index for coal waste recycling and the energy industry. To establish an accurate and efficient calorific value forecasting model, a method based on hybrid kernel function–support vector regression and genetic algorithms is presented in this paper. Firstly, key features of coal gangue gathered from major coal mines are measured and used to build a sample set. Then, the forecasting performance of single kernel function-based models is established, and linear kernel and Gaussian kernel functions are chosen according to forecasting results. Next, a hybrid kernel combined with the two kernel functions mentioned above is used to establish a calorific value forecasting model. In addition, a genetic algorithm is introduced to optimize critical parameters of SVR and the adjustable weight. Finally, the forecasting model based on hybrid kernel function–support vector regression and genetic algorithms is built to predict the calorific value of new coal gangue samples. The experimental results indicate that the hybrid kernel function is more suitable for forecasting the calorific value of coal gangue than that of a single kernel function. Moreover, the forecasting performance of the proposed method is better than other conventional forecasting methods.

Keywords: coal gangue; calorific value forecasting; support vector regression; hybrid kernel function; genetic algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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