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基于遗传算法和神经网络的结构损伤识别研究

Research on Structural Damage Identification Based on Genetic Algorithm and Neural Networks

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【作者】 张治国张谢东

【Author】 ZHANG Zhi-guo, ZHANG Xie-dong(College of Communications, Wuhan University of Technology, Hubei, Wuhan 430063, China)

【机构】 武汉理工大学交通学院武汉理工大学交通学院 湖北武汉430063湖北武汉430063

【摘要】 应用遗传算法来优化神经网络的连接权值,在此基础上提出了基于遗传算法和神经网络的结构损伤诊断方法,并以一个矩形截面简支钢梁的损伤识别为例,进行了实例应用研究。该方法弥补了传统的BP神经网络收敛速度慢,易陷入局部极小点等缺陷。研究结果表明遗传算法和神经网络结合后兼有神经网络广泛的映射能力和遗传算法快速的全局收敛性能。

【Abstract】 The article puts forward a new method using genetic algorithm to optimize neural networks’ weights, and a structural damage identification method based on genetic algorithm and neural networks is given on the foundation. Furthermore, a simple supported rectangle steel beam model is presented as a calculated example for applying the above-mentioned method. The method remedies the defects of the traditional BP neural networks such as restraining on calculating speed slowly and falling into the partly extreme minimum value easily and so on. The research results show that the extensive mapping ability of neural networks and the rapid and global convergence of genetic algorithm can be acquired simultaneously by combining them together.

【基金】 国家自然科学基金项目(10372075)
  • 【文献出处】 水利与建筑工程学报 ,Jorunal of Water Resources and Architectural Engingeering , 编辑部邮箱 ,2005年03期
  • 【分类号】R318.0;TP183
  • 【被引频次】24
  • 【下载频次】261
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