 Financial warning for coal mining investments: Evidence from the fruit fly optimisation algorithm with backpropagation neural networksXiaocong Ren, Zilong Huang and Yiqun He Energy Economics, 2024, vol. 134, issue C Abstract: Venture capital firms may be unable to withstand the high investments and risks associated with coal mining exploration due to limitations in the funding scale. Risk control capability is also a challenge for venture capital companies. Finding a balance between high-risk and high-return coal mining exploration projects is a problem that venture capital companies must face. We propose a financial risk-warning model for coal mining investment enterprises based on the fruit fly optimisation algorithm (FOA) with the backpropagation neural network (BPNN). The fusion of standardised and dimensionless sample data through factor analysis reduces the input dimension of the BPNN and improves its stability. The financial warning algorithm of the model has been effectively validated through experiments. The research results indicate that its accuracy has reached a high level of financial warning, reaching a level of 95%. Keywords: Coal mining investment; Financial risk-warning model; Venture capital firms; Backpropagation neural network; Fruit fly optimisation algorithm (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:134:y:2024:i:c:s0140988324003025 DOI: 10.1016/j.eneco.2024.107594 Access Statistics for this article Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant More articles in Energy Economics from Elsevier |
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