摘要
基于三层BP神经网络和层状弹性理论,由路表变形反算土基回弹模量。利用层状弹性计算程序构建了土基回弹模量与路表弯沉数据库,并输入BP神经网络进行训练,建立了基于BP神经网络的土基回弹模量反算模型。理论和实测路表弯沉反算结果表明,该方法具有良好的识别能力和泛化能力,是一种实用而有效的方法,为进一步快速、有效地评定土基的承载能力提供了依据。
Based on a 3-layer BP artificial neural network and the layered elastic moduli was backcalculated by the surface deflections. The database of s moduli and surface deflections were established using layered elastic calculation program. Backcalculation model of subgrade resilient moduli was developed after the BP artificial neural network was trained by the established database. The results of backcal culation by theoretical and measured surface deflections indicate thatthe ability of this approach to re-recognition and generation is satisfactory and it is a simple and practical method. It provides evidences to rapidly and effective- ly evaluate the bearing capacity of subgrade.
出处
《科学技术与工程》
2007年第5期806-809,815,共5页
Science Technology and Engineering
基金
国家自然科学基金项目(50278037)资助
关键词
BP神经网络
土基回弹模量
反算
层状弹性理论
落锤式弯沉仪
BP artificial neural network subgrade resilient moduli backcalculation layered elastictheory Failing Weight Deflectometer