基因表达式程序设计方法在采煤工作面瓦斯涌出量预测中的应用

基因表达式程序设计是一种基于基因组和表现型组的新型遗传算法，该算法在运行时具有很高的效率，实验表明在求解很多问题的时候比遗传规划优越两个数量级以上．预测采煤工作面瓦斯涌出量是进行通风设计和制定矿井安全技术措施的重要依据，而影响采煤工作面瓦斯涌出量的各因素之间关系不明确．基因表达式程序设计比较适合于求解这一类复杂的非线性问题．本采用基因表达式程序设计，建立了采煤工作面瓦斯涌出量的预测模型．结果表明，预测结果比遗传规划得到的结果具有更高的预测精度和很好的稳定性．章最后指出了该方法具有广泛的应用前景．

Application of Gene Expression Programming in Predicting the Amount of Gas Emitted from Coal Face

Gene expression programming ( GEP) is a kind of newly invented genotype/phenotype based genetic algorithms (GAs). GEP outperforms genetic programming (GP) more than two orders of magnitude in many fields. The prediction of the amount of gas emitted from coalfaces is the basis of ventilation system design and safety measurement implementation. Because the relationships among the ingredients, which have influence on the amount of gas emitted from coalface, are ambiguous, GEP does well in solving this kind of problems. In this paper, GEP is applied in the modeling of the amount of gas emitted from coalface. The result shows that the model found by GEP is more accurate as well as stable than the one found by GP.