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Rule-based expert system to assess caving output ratio in top coal caving
HaiYan Jiang1, Qinghui Song2, Kuidong Gao3
1Tai-an School, Shandong University of Science & Technology, Tai-an, Shandong, China.
Plos One
|September 4, 2020
Summary
This study introduces an automated system for assessing top coal release rate in coal mining. The adaptive Takagi-Sugeno fuzzy system with the Levenberg-Marquardt algorithm improves accuracy and reduces manual errors.
Area of Science:
- Mining Engineering
- Artificial Intelligence
- Computational Science
Background:
- Manual assessment of top coal release rate in coal mining is labor-intensive and prone to errors.
- Accurate assessment is crucial for improving coal recovery and quality.
Purpose of the Study:
- To develop an automated system for precise top coal caving output ratio assessment.
- To enhance the efficiency and reliability of top coal release rate evaluation in mining operations.
Main Methods:
- Utilized an adaptive Takagi-Sugeno (T-S) fuzzy system.
- Employed the Levenberg-Marquardt (LM) algorithm to optimize system parameters and damping factor.
- Compared performance using Pearson correlation coefficient, Coefficient of Determination, and relative error.
Main Results:
- The adaptive parameter Takagi-Sugeno method demonstrated improved accuracy in assessing the caving output ratio.
- The LM algorithm effectively adjusted the damping factor to minimize the objective function, enhancing iterative convergence.
- Robust evaluation confirmed the superiority of the adaptive T-S fuzzy system over the standard T-S method.
Conclusions:
- The developed system offers a more accurate and reliable method for top coal release rate assessment in coal mining.
- Automation of this process mitigates human error and increases operational efficiency.
- This approach holds significant potential for optimizing coal recovery and quality in mining industries.
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