| 基于Hopfield网的煤与瓦斯突出分类模型 |
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| 引用本文： | 高雷阜,徒君,赵艳艳.基于Hopfield网的煤与瓦斯突出分类模型[J].辽宁工程技术大学学报(自然科学版),2005,24(6):818-820. |
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| 作者姓名： | 高雷阜 徒君 赵艳艳 |
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| 作者单位： | 辽宁工程技术大学,应用数学研究所,辽宁,阜新,123000;辽宁工程技术大学,应用数学研究所,辽宁,阜新,123000;辽宁工程技术大学,应用数学研究所,辽宁,阜新,123000 |
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| 基金项目： | 辽宁省自然科学基金资助项目(20042176)
辽宁省教育厅基金资助项目(20040174) |
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| 摘 要： | 针对原有Hopfleld网学习算法的局限性，利用Hopfield网的非线性逼近能力来模拟煤与瓦斯突出中各指标的复杂非线性关系，通过联想记忆功能对煤与瓦斯突出进行分类。引入一种基于混合混沌法的学习算法，较快较好地训练了网络。将煤与瓦斯突出分类指标化分等级，进行编码，基于混合混沌法训练Hopfield网，建立煤与瓦斯突出分类模型。通过实验检验，证明了此模型的实用性。
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| 关 键 词： | Hopfield网 混合混沌 煤与瓦斯突出 分类 |
| 文章编号： | 1008-0562(2005)06-0818-03 |
| 修稿时间： | 2002年8月24日 |
Coal and gas outburst classifying model based on Hopfield |
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| GAO Lei-fu,TU Jun,ZHAO Yan-yan.Coal and gas outburst classifying model based on Hopfield[J].Journal of Liaoning Technical University (Natural Science Edition),2005,24(6):818-820. |
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| Authors: | GAO Lei-fu TU Jun ZHAO Yan-yan |
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| Abstract: | In order to overcome the weakness of Hopfield learning, using the nonlinear approaching ability of Hopfield, nonlinear relations of indexes in coal and gas outburst are simulated and the species of coal and gas outburst are classified by association- memory. A learning arithmetic is introduced based on CTSA, Hopfield is trained preferably and rapidly. Through grading the indexes of coal and gas outburst and coding Hopfield is trained and the models about coal and gas outburst are classified. Experiments prove the practicability of this model. |
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| Keywords: | Hopfield CTSA coal and gas outburst classifying |
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