遗传算法在非平稳动态系统模型变化点估计中的应用

Thafer R. Al-Badrany, Najlaa S. Al-Sharaby
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引用次数: 0

摘要

本研究采用了非平稳动态系统的一种诊断方法,即数据分割。非平稳系统的识别问题从轮廓诊断开始,它被认为是达到更适合描述系统的模型的基石。然后进行数据分割操作,将输入输出序列分割成时间间隔,以便在每个时间间隔内获得稳定的数据。数据分割损失函数
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Genetic Algorithm for Estimating Change Point in One Non-Stationary Dynamic Systems Model with Application
: One of the diagnostic methods for non-stationary dynamic systems was used in this research , namely data segmentation. The identification problem for non-stationary systems starts from the outline diagnostic, which considered as the cornerstone of reaching a model that is more appropriate in describing the system . Consequently the data segmentation operation is performed, were the input and output series are segmented into time intervals so that stable data can be obtained within each interval. data segmentation loss function
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