摘要
针对连续刚构桥进行参数优化,研究了边中跨比值、梁底曲线指数、跨高比和薄壁墩墩身间距这四个参数对连续刚构桥受力性能的影响。运用正交设计法、遗传算法、遗传算法与神经网络结合以及神经网络、遗传算法与正交表结合四种方法进行多目标优化计算,计算过程中考虑了施工阶段及混凝土用量的影响,并将四种方法进行了比较。结果表明单纯的遗传算法容易早熟,很难产生最优解。将遗传算法、神经网络和正交表结合效率较高且能够得到在经验范围之内的精度较好的优化结果。
Based on the continuous frame bridge,the parameter optimizations are considered. In this paper, the ratio of side-span and mid-span, the index of web-line ,the ratio of mid-span and depth of beam at the middle, and the space of two thin pier columns are all considered to determine the behavior of the continuous frame bridge under the construction load. Multi-object algorithms are used in the cross test design table,the combination of artificial neural network and genetic algorithm program and the combination of artificial neural network, genetic algorithm and cross test design table. The computation has considered the amount of concrete in the process of construction of the bridge, and compared the result of the four methods. The results tell us that using genetic algorithm only can be premature and hard to receive the best results. The combination of genetic algorithm ,artificial neural network and cross test table can be high efficient and high precision.
出处
《公路工程》
2008年第1期74-80,共7页
Highway Engineering
关键词
连续刚构桥
遗传算法
神经网络
正交设计
优化设计
Continuous frame bridge
the genetic algorithm
the artificial neural network
the cross test design
Optimal design