| 分级加载下岩土流变的神经网络模型 |
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| 引用本文： | 宋飞,赵法锁.分级加载下岩土流变的神经网络模型[J].岩土力学,2006,27(7):1187-1190. |
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| 作者姓名： | 宋飞 赵法锁 |
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| 作者单位： | 长安大学,地质工程系,西安,710054 |
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| 摘 要： | 针对分级加载下用线性叠加原理来描述岩土非线性流变存在的问题,采用人工神经网络方法代替传统数学力学方法,建立了分级加载下岩土流变的神经网络模型,并且对具体岩石的蠕变试验曲线进行了模拟.结果表明,该模型能较好地描述岩土的非线性流变,具有较强的泛化能力,为研究岩土的流变特性特别是分级加载下岩土的非线性流变特性提供了一条新途径.
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| 关 键 词： | 流变 分级加载 非线性 神经网络 模型 |
| 文章编号： | 1000-7598-（2006）07-1187-04 |
| 收稿时间： | 2004-10-11 |
| 修稿时间： | 2005-04-25 |
Neural network model for rheology of rock and soil under step loading |
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| SONG Fei,ZHAO Fa-suo.Neural network model for rheology of rock and soil under step loading[J].Rock and Soil Mechanics,2006,27(7):1187-1190. |
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| Authors: | SONG Fei ZHAO Fa-suo |
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| Institution: | Department of Geology Engineering, Chang’an University, Xi’an 710054, China |
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| Abstract: | In light of the problem of describing nonlinear rheology of rock and soil with principle of linear superposition, a neural network model for rheology of rock and soil under step loading has been established with artificial neural network instead of traditional mathematical and mechanical methods. By simulating the experimental creep curves of gypsum breccias, it is shown that the model can effectively describe nonlinear rheology of rock and soil with better prediction. This approach provides a new way for studying rheologicat properties of rock and soil especially nonlinear rheological properties under step loading. |
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| Keywords: | rheology step loading nonlinearity neural network model |
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