| PSO-RBFNN模型及其在岩土工程非线性时间序列预测中的应用 |
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| 引用本文： | 梁桂兰,徐卫亚,何育智,赵延喜.PSO-RBFNN模型及其在岩土工程非线性时间序列预测中的应用[J].岩土力学,2008,29(4):995-1000. |
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| 作者姓名： | 梁桂兰 徐卫亚 何育智 赵延喜 |
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| 作者单位： | 1. 河海大学,岩土工程研究所,南京,210098
2. 南京市民用建筑设计研究院有限责任公司,南京,210002 |
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| 基金项目： | 国家自然科学基金
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国家重点基础研究发展计划(973计划) |
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| 摘 要： | 岩土工程受力变形演化是一个典型的非线性问题，其演化的高度非线性和复杂性，很难用简单的力学、数学模型描述，但可用粒子群优化径向基神经网络对岩土工程应力、位移非线性时间序列进行动态实时预测。网络径向基层的单元数通过均值聚类法确定后，所有其它参数：中心位置、形状参数、网络权值，均通过粒子群优化算法在全局空间优化确定。工程实例应用表明，该模型预测结果准确、精度高，有良好的应用前景。
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| 关 键 词： | 粒子群优化 径向基神经网络 岩土工程 非线性时间序列 预测 |
| 文章编号： | 1000-7598-(2008)04-995-06 |
| 收稿时间： | 2006-05-15 |
| 修稿时间： | 2006年5月15日 |
Study and application of PSO-RBFNN model to nonlinear time series forecasting for geotechnical engineering |
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| LIANG Gui-an,XU Wei-ya,HE Yu-zhi,ZHAO Yan-xi.Study and application of PSO-RBFNN model to nonlinear time series forecasting for geotechnical engineering[J].Rock and Soil Mechanics,2008,29(4):995-1000. |
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| Authors: | LIANG Gui-an XU Wei-ya HE Yu-zhi ZHAO Yan-xi |
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| Institution: | 1. Research Institute of Geotechnical Engineering , Hohai University, Nanjing 210098, China; 2. Nanjing Municipal Institute of Civil Architecture Co., Ltd, Nanjing 210002, China |
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| Abstract: | Due to the nonlinearity and complexity of deformation evolution of geotechnical engineering , it is difficult to describe it with simple mechanical and mathematical model. A method for forecasting the stress and displacement nonlinear time series is proposed based on constructing radial basis function neural network using particle swarm optimization algorithm .After determination of units’ number in RBF layer using k-means, all parameters such as central position, shape parameter and weights of RBFNN are estimated dynamically in global with particle swarm optimization. The engineering case studies reveal that this model has high accuracy and a good prospect for nonlinear time series forecasting of geotechnical engineering. |
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| Keywords: | particle swarm optimization radial basis function neural networks geotechnical engineering nonlinear time series forecast |
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