Approximation techniques for application of genetic algorithms to structural optimization 近似技术在遗传算法和结构优化设计中的应用
Once more a very good source of information about connections between different approximation techniques 再一次推荐,这是一篇解释不同估计法彼此间关联的优良资讯来源。
Wavelets , an approximation technique that has received increasing attention in the last decade , are briefly reviewed 这堂课将简要的探讨近十年来逐渐被注意的近似值演算微波分析法。
2 . a new structural optimization algorithm combined with the half - determined ga and the hybrid approximation techniques is proposed 利用混合近似技术和对偶理论,建立了一般的基于遗传算法的结构优化设计的框架。
From the computational perspective , we can avoid to solve linear systems often suffering from ill conditioning , which was needed in former fractal approximation techniques 从计算前景看这避免了处理在以前的分形逼近方法中需要处理的病态线形系统。
It is well known that the wavelet liner approximation ( i . e , truncating the high frequencies ) can be approximate smooth singals very efficiently . however , for example , piecewise continous signals with large jump in signal value or in its derivatives , standard wavelet linear approximation techniques cannot achieve similar results for signals which are not smooth . to overcome these problems within the standard wavelet transform framework , the paper proposed the double adaptive wavelet transforms 众所周知,小波的线性近似(只用低频系数而不采用高频系数进行重构的方法称为线性近似)能非常有效的近似初始的光滑信号。然而对于非光滑信号,例如具有跳变点的分段连续信号,标准小波的线性近似就不能获得如光滑函数那样好的结果。