摘要
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。
The classical artificial ant colony algorithm is used to optimize the general artificial ant colony algorithm by introducing the chaos theory of monomer, and an artificial intelligence ant colony which takes the effective stress of the coal body,the internal and external gas pressure, the temperature and the gas adsorption force as input algorithm gas permeability prediction model.The model was trained with 15 sets of data by triaxial servo percolation device, and the experimental results were observed after 2 000 iterations.The results show that the maximum relative error is within 3.5%, and the test curve is fit well.
出处
《煤炭技术》
北大核心
2017年第6期171-173,共3页
Coal Technology
关键词
人工智能
蚁群算法
预测模型
artificial intelligence
ant colony algorithm
prediction model
