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JACIII Vol.30 No.2 pp. 424-432
(2026)
doi: 10.20965/jaciii.2026.p0424

Research Paper:

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Operating Parameters Optimization Based on BPNN and NSGA-III in Rotating Mode for Pneumatic Directional Drilling

Hao Li*1,*2, Lijuan Fan*3,*4,*5 ORCID Icon, Ningping Yao*1,*2,†, Hongchao Wei*2, and Chengda Lu*4,*5,*6 ORCID Icon

*1China Coal Research Institute
No.5 East Qingnian Gou Road, Hepingli, Chaoyang District, Beijing 10013, China

*2China Coal Technology Engineering Group (CCTEG) Xi’an Research Institute (Group) Co., Ltd.
No.82 Jinye 1st Road, Gaoxin District, Xi’an, Shaanxi 710077, China

*3School of Future Technology, China University of Geosciences
No.388 Lumo Road, Hongshan District, Wuhan, Hubei 430074, China

*4Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems
No.388 Lumo Road, Hongshan District, Wuhan, Hubei 430074, China

*5Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education
No.388 Lumo Road, Hongshan District, Wuhan, Hubei 430074, China

*6School of Artificial Intelligence and Automation, China University of Geosciences
No.388 Lumo Road, Hongshan District, Wuhan, Hubei 430074, China

†Corresponding author

Received:
June 16, 2025
Accepted:
October 11, 2025
Published:
March 20, 2026
Creative Commons License
Keywords:
directional drilling, multi-objective optimization, BPNN, NSGA-III, operating parameters
Abstract

Drilling operations face the problems of low drilling efficiency and more difficult slag discharge in coal seams. A multi-objective optimization method is proposed to solve these problems. Rate of penetration (ROP), air pressure, and pull-out pressure are determined as the optimization objectives by characterization of the rotating mode. The maximum information coefficient (MIC) method is used to select the decision variables related to the optimization objectives, which are feed pressure, air volume, borehole depth, coal seam hardness, and rotary pressure. Then, a multi-objective optimization model is established using back propagation neural network (BPNN). The Non-Dominated Sorting Genetic Algorithm-III (NSGA-III) is used to solve the optimal operating parameters when the ROP is maximum and the air pressure and the pull-out pressure are minimum. Comparative experiments show that the method proposed in this study is effective. The results of this study can provide a new solution to improving drilling efficiency and resolving slag discharge difficulties in coal mines.

Overall scheme of operating parameters optimization

Overall scheme of operating parameters optimization

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Cite this article as:
H. Li, L. Fan, N. Yao, H. Wei, and C. Lu, “Operating Parameters Optimization Based on BPNN and NSGA-III in Rotating Mode for Pneumatic Directional Drilling,” J. Adv. Comput. Intell. Intell. Inform., Vol.30 No.2, pp. 424-432, 2026.
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Last updated on Mar. 19, 2026