Big Data Analysis of Energy Economics in Coal Market

Hui Liu (), Nikolaos Nikitas (), Yanfei Li () and Rui Yang ()
Additional contact information
Hui Liu: Central South University
Nikolaos Nikitas: University of Leeds
Yanfei Li: Hunan Agricultural University
Rui Yang: Central South University

Chapter Chapter 3 in Big Data in Energy Economics, 2022, pp 67-94 from Springer

Abstract: Abstract Coal is known as industrial food and black gold, and its price changes not only affect the production and operation of the coal industry, but also affect the country's investment, consumption, import and export, and overall economic development. This chapter introduces the important role of coal in the field of energy economics and analyzes the factors that influence coal price fluctuations. Then, through correlation analysis, this chapter selects several variables that have a strong relationship with coal price changes to conduct multi-input multi-output coal price prediction modeling. The effects of decomposition method and Boosting method on model prediction accuracy are compared. Finally, the chapter concludes with an econometric analysis of international coal markets and big data technologies, and proposes policy recommendations for energy economic development in this context.

Keywords: Coal prices forecasting; Big data modeling; Multi-factor analysis; Hybrid ensemble model; International coal market; Policies and recommendations (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:mgmchp:978-981-16-8965-9_3

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DOI: 10.1007/978-981-16-8965-9_3

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