Forecasting manufacturing industrial natural gas consumption of China using a novel time-delayed fractional grey model w
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Forecasting manufacturing industrial natural gas consumption of China using a novel time-delayed fractional grey model with multiple fractional order Yu Hu1,5 · Xin Ma1,2
· Wanpeng Li3 · Wenqing Wu1 · Daoxing Tu4
Received: 2 June 2019 / Revised: 7 August 2020 / Accepted: 21 August 2020 © SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2020
Abstract Improving the proportion of natural gas consumption of the manufacturing industry would make significant contributions to the low-carbon and sustainable development of China, which is one of the largest manufacturers in the world. However, it is very difficult to catch the trend of natural gas consumption of the concerning manufacturing industry as not enough trustable data can be collected. To fill this gap, a novel time-delayed fractional grey model is developed to forecast the natural gas consumption concerning time-delayed effect. Theoretical analysis shows it has more general formulation, unbiasedness and higher flexibility than the existing similar model. Being optimized by the Particle Swarm Optimization algorithm, the proposed model presents higher accuracy in four validation cases. Finally, it is used to forecast the natural gas consumption of the manufacturing industry of China, and the results show that the proposed model significantly outperforms the other seven existing grey models. Keywords Green manufacturing · Natural gas consumption · Low-carbon production · Time-delayed grey model · Fractional grey model · Particle swarm optimization Mathematics Subject Classification 91B84
Communicated by Vasily E. Tarasov.
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Xin Ma [email protected]
1
School of Science, Southwest University of Science and Technology, Mianyang, China
2
State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, China
3
School of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, Manchester, UK
4
School of Science, Southwest Petroleum University, Chengdu, China
5
College of Mathematics and Statistics, Chongqing University, Chongqing, China 0123456789().: V,-vol
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1 Introduction The manufacturing industry can directly reflect a country’s productivity level, and energy is an important material basis for human survival and development. According to Ref National bureau of statistics (2002), in the past decade, the total energy consumption of the manufacturing industry has been on a steady trend, accounting for about 57% of the total energy consumption of the whole country; however, the gross domestic product (GDP) of the manufacturing industry only accounts for about 31% of the total, showing a sharp downward trend. It shows that the energy consumed by the manufacturing industry is not proportional to its contribution to the national GDP, and the consumption structure of the manufacturing energy needs to be further improved. Natural gas is a kind of high-quality, efficient, and clean low-carbon energy. With the reform of natural ga
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