| 利用神经网络法进行直接顶的分类 |
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| 引用本文： | 邢纪波,俞良群,张国华,祁轶军,王泳嘉.利用神经网络法进行直接顶的分类[J].黑龙江科技学院学报,1994(2). |
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| 作者姓名： | 邢纪波 俞良群 张国华 祁轶军 王泳嘉 |
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| 作者单位： | 黑龙江矿业学院土木工程系(邢纪波，俞良群，张国华，祁轶军)，东北大学(王泳嘉) |
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| 摘 要： | 针对标准B-P神经网络算法存在学习速度慢的问题提出了改进算法。将改进后的神经网络模型应用于直接顶分类,不论是直接顶初次跨落步距的拟合值还是其预测值,神经网络法的计算精度均高于多元线性回归法。
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| 关 键 词： | 直接顶分类 人工神经网络 B-P学习算法 非线性建模 |
CLASSIFY THE IMMEDIATE ROOF BASED ON ARTIFICIAL NEURAL NETWORK |
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| Xing Jibo,Yu Liangqun,Zhang Guohua,Qi Yijun.CLASSIFY THE IMMEDIATE ROOF BASED ON ARTIFICIAL NEURAL NETWORK[J].Journal of Heilongjiang Institute of Science and Technology,1994(2). |
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| Authors: | Xing Jibo Yu Liangqun Zhang Guohua Qi Yijun |
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| Institution: | Xing Jibo Yu Liangqun Zhang Guohua Qi Yijun(Civil Engineering)Wang Yongjia(Northeastern University) |
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| Abstract: | The widely used conventional B-P neural network has been improved to speed up the training process. The new proposed neural network is used to study the classification problem of immediate roof. Be it the approximated caving step or the predicted caving step, the proposed neural network is better in accuracy than the multi-variate linear regression method. |
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| Keywords: | classification of immediate roof artifical neural network B-P learning algorithm non-linear modelling |
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