摘要
采用人工神经网络较强的非线性映射能力和学习能力 ,提出基于人工神经网络的高速公路软土地基最终沉降量的预测新方法。本方法利用实测资料直接建模 ,避免了传统方法计算过程中各种人为因素的干扰 ,所建立的模型预测精度高、简便易行 ,因而具有广泛的工程实用价值。
A new method for evaluating final settlement of soft ground for expressway is presented in this paper, by use of the strong nonlinear mapping and learning ability of artificial neural networks. Since the model of this method is directly based on real samples, it can avoid the mistakes due to factitiousness in traditional methods. It is proved that the prediction model is accurate and easy to operate, so the method has widely practical engineering value.
出处
《公路交通科技》
CAS
CSCD
北大核心
2000年第6期15-18,共4页
Journal of Highway and Transportation Research and Development
基金
广东省自然科学基金资助(990148)
广东工业大学青年基金资助(98033)
