一种求解结构可靠度的新型计算方法

提出了一种求解结构可靠度的软计算方法,该方法综合了人工神经网络的柔软性和遗传算法的全局性及并行快速性的优点.利用人工神经网络的柔软性,可以生成任意形状的函数,因而可以更加贴切地拟合功能函数;由于遗传算法具有并行处理能力,可以对多组样本同时进行处理,因此收敛速度加快.除此之外,文中的遗传算法还使用了小生境共享技术,有效地克服了陷入局部解的缺陷.并根据上述方法研制了结构可靠度分析的电算程序,算例计算表明,计算结果具有很高的精度,该算法为结构可靠度研究提供了一种新的思路和实现路径.

A new method to calculate the structure reliabilitty

A soft computing algorithms for structure reliability is developed.In the algorithm,the softness of artificial neural networks and the global property and parallelism of genetic algorithms are combined.Making use of the softness of artificial neural networks,the function of any shape can be produced.So it can be appropriate fit with the performance function.Due to the parallelism of genetic algorithms,it can deal with many samples in the same time.So the velocity of convergence is accelerated.In addition,the niche sharing technology of genetic algorithms overcomes the deficiency of easily falling into local solutions.The program of structure reliability analysis is developed according to the proceeding algorithms.The example shows that the calculating results have high precision.And it gives a new idea and a new way to the structure reliability analysis.