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利用经典人工智能生物蚁群算法,引入单体混沌理论对一般的人工蚁群算法进行优化,构建了以煤体有效应力、瓦斯气体内外压力、温度、气体吸附力为输入的人工智能蚁群算法瓦斯渗透率预测模型。利用三轴伺服渗流装置取15组数据对模型进行训练,迭代2 000次后观察实验结果。测试结果最大相对误差在3.5%以内,测试曲线拟合很好。
Using the classical artificial intelligence biological ant colony algorithm, the introduction of monomer chaos theory to optimize the general artificial ant colony algorithm to build an artificial intelligence ant colony algorithm with the effective stress of coal, gas pressure inside and outside, temperature, gas adsorption as input Gas permeability prediction model. Three groups of three-axis servo seepage device were used to train the model. After iterating 2,000 times, the experimental results were observed. The maximum relative error of the test results is within 3.5%, and the test curve fits well.