| 基于BCABC-SVM的边坡稳定性预测 |
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| 引用本文： | 胡军,王凯凯,董建华.基于BCABC-SVM的边坡稳定性预测[J].沈阳工业大学学报,2016,38(2):222-227. |
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| 作者姓名： | 胡军 王凯凯 董建华 |
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| 作者单位： | 辽宁科技大学 土木工程学院， 辽宁 鞍山 114051 |
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| 摘 要： | 为了准确地对边坡稳定性进行预测,采用支持向量机(SVM)建立边坡稳定性和影响因素之间的非线性关系.针对支持向量机参数对预测效果的影响,采用基于细菌趋化的蜂群算法(BCABC)对其进行优化选择,提出了边坡稳定性预测的细菌趋化的蜂群优化支持向量机模型.运用该方法对边坡实例进行预测,预测结果与边坡稳定性实际状态相吻合,结果表明,基于细菌趋化的蜂群优化支持向量机模型在边坡稳定性评价中具有一定的可靠性和有效性.
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| 关 键 词： | 边坡稳定 蜂群算法 细菌趋化 微粒群算法 自适应移动步长 支持向量机 参数选择 归一化处理 |
Forecasting of slope stability based on BCABC-SVM |
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| HU Jun,WANG Kai-kai,DONG Jian-hua.Forecasting of slope stability based on BCABC-SVM[J].Journal of Shenyang University of Technology,2016,38(2):222-227. |
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| Authors: | HU Jun WANG Kai-kai DONG Jian-hua |
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| Affiliation: | School of Civil Engineering, University of Science and Technology Liaoning, Anshan 114051, China |
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| Abstract: | In order to accurately forecast the slope stability, the nonlinear relationship between the slope stability and its influencing factors was established with adopting the support vector machine （SVM）. Aiming at the effect of SVM parameters on the forecasting effect, the parameters were optimized and selected with bee colony algorithm based on bacterial chemotaxis （BCABC）, and the BCABC SVM model for the slope stability was proposed. This method was used to forecast the slope instance. The forecasting results are consistent with the actual states of slope stability. The results show that the BCABC SVM model has a certain reliability and validity in the evaluation of slope stability. |
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| Keywords: | slope stability bee colony algorithm bacterial chemotaxis particle swarm optimization algorithm adaptive mobile step length support vector machine （SVM） parameter selection normalization processing |
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