Abstract
Mine water that inrushes from coal-roof strata has always posed a substantial threat to mining activities every year. Therefore, an accurate prediction of the water-conducting fracture zone (WCFZ) height in the mining overburden strata is of great significance for the prevention and control of mine water accidents. The support vector regression (SVR) is proposed to predict the height of the WCFZ based on the mining depth, hard rock proportional coefficient, mining thickness and length of the working face. Simultaneously, the multi-population genetic algorithm (MPGA) is employed to search for the optimal SVR parameters. The MPGA-SVR model is trained and tested with a total of 69 collected data samples, and it is also applied to a field test. The accuracy and stability of the model were measured by the mean squared error and correlation coefficients. The obtained results show that the MPGA-SVR model achieves a higher accuracy and stability than the traditional empirical formula and genetic algorithm (GA)-SVR model. In terms of the process for optimizing the SVR parameters, the MPGA can find the optimal parameters more quickly and accurately, and it can effectively overcome the problem of premature and slow convergence of the genetic algorithm (GA). The proposed model improves the prediction accuracy and stability, which will help to avoid accidents caused by the inrush of water inrush in mining overburden strata and protect the ecological environment of the mining area.
Highlights
As an important fossil energy source, coal has always played a dominant role in China’s primary energy consumption structure [1,2]
Accurately predicting the height of the water-conducting fracture zone (WCFZ) in the mining overburden strata is of great significance for the safe production of coal mining [6,7,8]
The support vector regression (SVR) is an application model of a support vector machine (SVM), which was proposed by Vapnik (2000) [28]
Summary
As an important fossil energy source, coal has always played a dominant role in China’s primary energy consumption structure [1,2]. In the process of mining activities, the equilibrium state of the original rock stress in the overburden strata is destroyed, which leads to collapse, fracture and bending in the mining overburden strata. In the GA evolution process, the choice of the crossover and mutation probability often determines the global search performance of the algorithm and the balance with the local search ability. The GA has the disadvantage of slow convergence; that is, it fluctuates as it approaches the optimal solution but does not converge quickly To deal with this problem, the concept of information theory has been introduced to preventing from premature convergence. To make full use of the global evolutionary characteristics of the GA and avoid its shortcomings, the multi-population genetic algorithm (MPGA) is first adopted to establish an MPGA-SVR model for predicting the height of the WCFZ. The empirical formula and GA-SVR were adopted to predict the height for comparison
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
