| 矿井瓦斯涌出量的径向基函数网络预测模型 |
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| 引用本文： | 陈连军,粟才全.矿井瓦斯涌出量的径向基函数网络预测模型[J].山东科技大学学报(自然科学版),2009,28(4):93-96,101. |
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| 作者姓名： | 陈连军 粟才全 |
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| 作者单位： | 1. 山东科技大学,矿山灾害预防控制教育部重点实验室,山东,青岛,266510
2. 山东科技大学,矿山灾害预防控制教育部重点实验室,山东,青岛,266510;林东矿业集团有限公司,贵州,贵阳,550056 |
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| 摘 要： | 为进一步研究瓦斯涌出量与影响因素之间的映射关系，建立了径向基函数网络预测模型，并基于瓦斯涌出量与影响因素关系的实际收集数据，对其本构关系进行了函数逼近，通过网络所建立的映射关系对矿井瓦斯涌出量进行了预测。实例分析表明，利用RBF网络预测矿井瓦斯涌出量，拟舍精度较高，与BP网络相比较，具有较高的预测效率和精度。
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| 关 键 词： | 瓦斯涌出量预测 本构关系 径向基函数 神经网络 |
Prediction Model for Mine Gas Emission Volume with Radial Basis Function Network |
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| CHEN Lian-jun,SU Cai-quan.Prediction Model for Mine Gas Emission Volume with Radial Basis Function Network[J].Journal of Shandong Univ of Sci and Technol: Nat Sci,2009,28(4):93-96,101. |
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| Authors: | CHEN Lian-jun SU Cai-quan |
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| Institution: | 1.Key Laboratory of Mining Disaster Prevention and Control;Ministry of Education;SUST;Qingdao;Shandong 266510;China;2.Lindong Mining Group Co.Ltd.;Guiyang;Guizhou 550056;China |
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| Abstract: | For the purpose of studying the mapping relationship between gas emission and influencing factors it established the prediction model with radial basis function network,collected the actual data based on the relationship between gas emission and influencing factors,and carried out the function approximation of its constitutive relation.The mine gas emission has been predicted by means of mapping relationship.A case study shows that the fitting precision of prediction of mine gas emission is quite acceptable... |
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| Keywords: | prediction of gas emission volume constitutive relation radial basis function neural network |
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