| 矿井瓦斯涌出量的遗传神经网络预测研究 |
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| 引用本文： | 乔维德,佟素顺.矿井瓦斯涌出量的遗传神经网络预测研究[J].江苏广播电视大学学报,2008,19(3):53-56. |
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| 作者姓名： | 乔维德 佟素顺 |
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| 作者单位： | 1. 常州市广播电视大学,江苏,常州,213001
2. 大同煤矿集团公司,山西,大同,037041 |
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| 摘 要： | 矿井瓦斯涌出系统是非线性变化的复杂系统，传统的瓦斯涌出量预测方法存在一定的局限性。根据改进遗传算法（IGA）和BP算法的特点，将两者结合起来，利用改进遗传算法优化BP网络权重和阈值，形成IGA-BP混合算法，用于对矿井瓦斯涌出量进行科学预测。检验结果表明，基于IGA-BP混合算法的遗传神经网络模型可靠，预测精度高，效果良好。
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| 关 键 词： | 遗传算法 神经网络 IGA-BP 瓦斯涌出量预测 |
Research on Forecast of Mine Gas Emission Based on Genetic Algorithm and Neural Network |
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| QIAO Wei-de,TONG Su-shun.Research on Forecast of Mine Gas Emission Based on Genetic Algorithm and Neural Network[J].Journal of Jiangsu Radio & Television University,2008,19(3):53-56. |
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| Authors: | QIAO Wei-de TONG Su-shun |
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| Institution: | QIAO Wei-de,TONG Su-shun(1. Changzhou Radio ＆ TV University, Changzhou 213001 ,Jiangsu, China; 2.Datong Coal Mine Group, Datong 037041, Shanxi, China) |
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| Abstract: | Mine gas emission system is a complex system and is also nonlinear change one.The traditional methods for the gas emission prediction have a certain limitations.According to the characteristics of the improved genetic algorithm(IGA) and BP algorithm,IGA and BPalgorithm are combined.By using optimization weights of the improved genetic algorithm and thresholds of BP network,the IGA-BP hybrid algorithm is formed for predicting mine gas emission.Experimental results show that the model for genetic neural network based on IGA-BP mixed algorithm is reliable,has high prediction accuracy and good effects. |
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| Keywords: | genetic algorithm neural networks IGA-BP gas emission forecast |
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