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针对矿井通风网络优化问题,借鉴文化算法的双层进化结构,提出一种递阶文化算法.算法种群空间采用分层遗传算法,引入递阶编码描述通风网络支路结构,并给出相应的不可行支路修复算子和可行调节支路阻值调节算子;信度空间采用统计学习方法提取公共优势支路作为知识,指导种群空间进化过程中的可调支路选取.仿真结果表明,该算法获得的最优控风方案满足控风要求,且所得方案的加阻值总和最小,所需调风成本更低.
Aimed at the mine ventilation network optimization problem, a hierarchical culture algorithm is proposed based on the two-layer evolutionary structure of cultural algorithm. The algorithm uses hierarchical genetic algorithm to introduce the hierarchical structure of the ventilation network branch, and gives the corresponding unacceptable Line tributary repair operator and feasible regulation tributary resistance adjustment operator; reliability space uses statistical learning method to extract the common tributary as knowledge to guide the selection of adjustable tributaries in the evolutionary process of population space.The simulation results show that the The optimal wind-control scheme obtained by the algorithm satisfies the requirement of wind-control, and the sum of the added resistances of the obtained scheme is the minimum, and the wind-control cost required is lower.