提高煤矿微震定位精度的台网优化布置算法

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Abstract For optimizing the large-scale network configuration of combinatorial optimization problem，a model，including the blocks of input data preparation，genetic algorithm and location capability assessment of network，is constructed to solve the establishment of optimal objective function of microseismic network layout. First，initial parameters are provided to genetic algorithm by the data preparation block based on the comprehensive index method and the general principle of choosing candidate points；and then the locating ability of the obtained solution is evaluated by the assessment block. In the block of genetic algorithm，natural number coding method is utilized to express the individual of microseismic network layout，in which winning candidates are in front of the losing to keep more information. Combining with the created penalty function，which is used to guarantee the capability of monitoring and recording weak tremor，the individual fitness function is built to evaluate the performance of network. In order to prevent the premature convergence of algorithm，crossover and mutation operators are mixed and operated in the range of containing winning candidates to increase computing efficiency. The application results from on-site and experiment show that，the genetic algorithm can quickly find the best solution and its computing time does not increase significantly with the expansion of combination. The network configuration solved by the genetic algorithm is better than the layout used currently，which is demonstrated by the numerical emulation technique，and significantly decrease the hypocenter location errors in the key monitoring areas；and the maximal reduction of location errors reach to 230 m.

Key words： mining engineering microseism network configuration genetic algorithm natural number coding penalty function fitness function

Received: 06 June 2011

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https://rockmech.whrsm.ac.cn/EN/Y2012/V31/I1/8

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