A hybrid sparrow optimization Kriging model and its application in geological modeling

With the proposal of intelligent mines, the demand for drilling is increasing daily. Therefore, it is particularly crucial to gather more geological data by interpolation of limited drilling data for subsequent three-dimensional geological modeling. In this paper, a hybrid sparrow optimization Krigi...

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Vydáno v:Scientific reports Ročník 14; číslo 1; s. 24610 - 19
Hlavní autoři: Shi, Xiaonan, Wang, Yumo, Wu, Haoran, Wang, Aoqian
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Nature Publishing Group UK 19.10.2024
Nature Publishing Group
Nature Portfolio
Témata:
639/705
639/705/117
Accuracy
Algorithms
Chaos theory
Coal
Coal mines
Coal mining
Drilling
Geology
Humanities and Social Sciences
Intelligence
Kriging
multidisciplinary
Optimization
Science
Science (multidisciplinary)
Sparrow optimization algorithm
Three-dimensional geological modeling
Drilling
Sparrow optimization algorithm
Three-dimensional geological modeling
Kriging
ISSN:2045-2322, 2045-2322
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Shrnutí:With the proposal of intelligent mines, the demand for drilling is increasing daily. Therefore, it is particularly crucial to gather more geological data by interpolation of limited drilling data for subsequent three-dimensional geological modeling. In this paper, a hybrid sparrow optimization Kriging model (HSSA), in which chaos theory and Levy flight are integrated into the initial population update algorithm of the sparrow algorithm and the location update algorithm of the entrants, is proposed. Next, the golden sine optimization algorithm is introduced into the reconnaissance and early warning mechanism of the sparrow algorithm to further improve the accuracy and local escape ability. By the correlation optimization of the original sparrow algorithm, the speed and accuracy of swarm intelligence optimization are further improved. In addition, the model solves the parameters of the variation function of the ordinary Kriging interpolation and reduces the generation error of the formation data interpolation. The results of relevant experiments show that the hybrid sparrow optimization Kriging model improves the accuracy and convergence speed compared with other swarm intelligence algorithms and that the accuracy of this model is improved by 8.4% compared with the original Kriging interpolation algorithm. Based on the hybrid sparrow optimization Kriging model, we propose a three-dimensional stratigraphic model for the Yangchangwan Coal Mine, which provides further support for mining operations and three-dimensional stratigraphic research in this area. The accuracy and applicability of the hybrid sparrow optimization Kriging model are further explained using a case study with the stratigraphic model data in the Yangchangwan Coal Mine. HSSA with significant potential for applications in industries such as coal mining and geological exploration. In these fields, the efficient acquisition, processing, and modeling of stratigraphic data are critical for enhancing geological interpretation and optimizing operational workflows.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-75347-8