| 基于ANFIS的单桩竖向极限承载力预测模型 |
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| 引用本文： | 杨 磊,徐洪钟.基于ANFIS的单桩竖向极限承载力预测模型[J].岩土力学,2006,27(Z1):822-825. |
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| 作者姓名： | 杨 磊 徐洪钟 |
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| 作者单位： | 南京工业大学 土木工程学院， 南京 210009 |
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| 基金项目： | 江苏省普通高校自然科学研究计划资助项目（No. 05KJB560040）；江苏省基础研究计划（自然科学基金）资助项目（No. BK2006565） |
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| 摘 要： | 人工神经网络已应用在岩土工程的各个方面。针对常用的BP网络的不足之处，建立了基于自适应神经模糊推理系统（ANFIS）的单桩竖向极限承载力预测模型。利用文献中桩的载荷试验数据来训练ANFIS网络，确定了网络参数。研究结果表明，同常用的BP网络相比，ANFIS预测模型具有学习速度快，拟合能力较好，训练结果唯一等优点，该方法是一种有效地预测单桩极限承载力的方法。
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| 关 键 词： | 单桩 竖向极限承载力 ANFIS 预测模型 |
| 收稿时间： | 2006-05-10 |
Predicting model of vertical ultimate bearing capacity of single pile using adaptive neuro-fuzzy inference system |
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| YANG Lei,XU Hong-zhong.Predicting model of vertical ultimate bearing capacity of single pile using adaptive neuro-fuzzy inference system[J].Rock and Soil Mechanics,2006,27(Z1):822-825. |
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| Authors: | YANG Lei XU Hong-zhong |
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| Institution: | College of Civil Engineering , Nanjing University of Technology, Nanjing 210009, China |
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| Abstract: | Artificial neural networks have been used in many areas in geotechnical engineering applications. Adaptive neuro-fuzzy inference system (ANFIS) is used to predict vertical ultimate bearing capacity of single pile. The data of pile load test obtained from a literature are used to train ANFIS network and to determine the network parameters. The results show that the proposed modeling approach outperforms classical back-propagation (BP) neural network in terms of computational speed, forecast errors, efficiency. ANFIS is an effective method to achieve both high accuracy and less computational complexity for predicting vertical ultimate bearing capacity. |
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| Keywords: | single pile vertical ultimate bearing capacity ANFIS predicting model |
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