Adaptive Weighted Case-Based Reasoning for Intelligent Coal Mine Decision Support Systems

Abstract

Under the background of intelligent transformation of coal mines, an intelligent decision support system based on case-based reasoning (CBR) has become crucial for improving production control. This paper constructs such a system and innovatively proposes an adaptive weight dynamic case retrieval algorithm (AWDCR). The algorithm leverages real-time monitoring of multi-source production data, dynamically adjusting case attribute weights based on data change characteristics and decision influence through a hybrid AHP-entropy weight mechanism. Using MATLAB simulation with 100,000+ actual production records across 100 scenarios (normal, equipment failure, environmental anomaly), results show AWDCR reduces average retrieval time by 20% and improves decision accuracy from 80% to 90% compared to traditional CBR. enhancing retrieval accuracy by 20%. The system effectively enhances production efficiency and safety, laying a foundation for intelligent coal mining.

References

H. Eroğlu, O. Kurtuluş, and O. Can. Decision making methods used for improving power quality to meet the sustainable energy targets. Energy & Environment, vol. 36(1), 499–539, 2025. https://doi.org/10.1177/0958305x241276829

P. M. Spanidis, F. Pavloudakis, and C. Roumpos. The Knowledge Management Landscape in the Greek Coal Mining Industry. Mining, Metallurgy & Exploration, 41(2), 819–841, 2024. https://doi.org/10.1007/s42461-024-00958-8

X. Zhang, J. Gao, K. Zhao, Y. Li, C. Li, and Z. Xie. Research on generation method of intelligent emergency preplan for coal mine accident. Mining Safety & Environmental Protection, 51(1), 78–85, 2024. http://doi.org/10.19835/j.issn.1008-4495.20230320

X. Ding, M. Hasanipanah, M. Monjezi, R. A. Abdullah, T. Nguyen, and D. V. Ulrikh. Enhancing mine blasting safety: developing intelligent systems for accurate flyrock prediction through optimized group method of data handling methods. Natural Resources Research, 34(2), 1199–1218, 2025. https://doi.org/10.1007/s11053-024-10445-y

L. Wei, M. Lei, Z. Xiancheng, T. Xianhui, and F. Quan. Research progress of the rotary steerable system and its control methods. Coal Geology & Exploration, 51(10), 167–179, 2023. htpp://doi.org/10.12363/issn.1001-1986.23.03.0137

T. Ye, M. Dong, Y. Liang, J. Long, Y. Zheng, and J. Lu. Online optimization of boiler operation based on information integration and case-based reasoning. International Journal of Green Energy, 20(1), 15–27, 2023. https://doi.org/10.1080/15435075.2021.2021417

Authors

  • Zhiqiang Zhang National Energy Group Ningxia Coal Industry Co., Ltd. Hongliu Coal Mine
  • Kai Tan Chongqing Institute of China Coal Technology & Engineering Group
  • Changjun Yang National Energy Group Ningxia Coal Industry Co., Ltd. Hongliu Coal Min
  • Yong Li Chongqing Institute of China Coal Technology & Engineering Group
  • Chunhua Huang Chongqing Institute of China Coal Technology & Engineering Group
  • Wei Li National Energy Group Ningxia Coal Industry Co., Ltd. Hongliu Coal Mine

DOI:

https://doi.org/10.31449/inf.v49i34.9666

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Published

08/26/2025

How to Cite

Zhang, Z., Tan, K., Yang, C., Li, Y., Huang, C., & Li, W. (2025). Adaptive Weighted Case-Based Reasoning for Intelligent Coal Mine Decision Support Systems. Informatica, 49(34). https://doi.org/10.31449/inf.v49i34.9666

Issue

Vol. 49 No. 34 (2025): Online-only issue

Section

Online-only

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