| 软基沉降的BP神经网络和灰色系统联合预测 |
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| 引用本文： | 周建伟,周爱国,刘晓.软基沉降的BP神经网络和灰色系统联合预测[J].地质科技情报,2005,24(Z1):109-111. |
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| 作者姓名： | 周建伟 周爱国 刘晓 |
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| 作者单位： | 1. 中国地质大学环境学院,武汉,430074
2. 湖北清江水电开发有限责任公司,湖北,宜昌,443000 |
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| 摘 要： | 使用BP神经网络插值方法对灰色数据进行了预处理,进而建立了预测软基沉降量的BP神经网络和灰色系统联合模型.实例分析表明,该模型短期沉降预测结果的最大相对误差小于2%,最终沉降预测结果的相对偏差小于5%,且灰色预测时取后期沉降瘦导颇算结果准确度高于取前期沉降数据的计算结果准确度.
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| 关 键 词： | 软基沉降 灰色理论 BP神经网络 |
| 文章编号： | 1000-7849(2005)S0-0109-03 |
| 修稿时间： | 2005年3月27日 |
BP Artificial Neural Network and Grey System United Model for Settlement Prediction of Soft Soil Foundation |
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| ZHOU Jian-wei,ZHOU Ai-guo,LIU Xiao.BP Artificial Neural Network and Grey System United Model for Settlement Prediction of Soft Soil Foundation[J].Geological Science and Technology Information,2005,24(Z1):109-111. |
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| Authors: | ZHOU Jian-wei ZHOU Ai-guo LIU Xiao |
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| Abstract: | The establishment of the BP artificial neural network and grey system united model and grey data pretreatment depends on BP artificial neural network interpolate. The analysis of illustration shows that the maximum opposite error of predicting short period settlement is less than 2% , and that of ultimate settlement is less than 5%. As for choosing settlement data aspect, the result accuracy of choosing late stage data is higher than that of choosing prophase data. |
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| Keywords: | soft soil foundation grey theory BP artificial neural network |
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