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煤与瓦斯突出是受诸多因素影响的复杂问题,为了提高其预测的准确性,本文以变精度粗糙集理论中的决策表为主要工具,首先将影响煤与瓦斯突出的检测信号作为预测的条件属性集,煤与瓦斯突出量作为对预测的决策属性,建立决策表,然后利用小生境遗传算法适合于进行多峰值函数优化的特点,提出了一种基于小生境遗传算法的粗糙集属性约简方法,用于求解决策表的多个约简,进而进行值约简后抽取出预测规则。算例结果说明了本算法的正确性和可行性。
Coal and gas outburst are complex problems affected by many factors. In order to improve the accuracy of the prediction, this paper takes the decision table in the variable precision rough set theory as the main tool. First, the detection signals that affect the coal and gas outburst are used as the prediction conditions Attribute set, coal and gas outburst as the decision attributes of the prediction, a decision table is established, and then the niche genetic algorithm is suitable for multi-peak function optimization. A rough set attribute reduction based on niche genetic algorithm Method for solving multiple reductions in a decision table and then extracting the prediction rules after value reduction. The results show that the algorithm is correct and feasible.