id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-20728	Shi, Mo; Xu , Xiaoyan; Choi, Yeol	Gaussian Analysis of the Elevator Traffic under the Typical Office Building	2024	8	.pdf	application/pdf	6253	269	35	By examining the performance of LS-SVMs in predicting elevator traffic and comparing it with actual monitored data, this study underscores the effectiveness and rationality of using LS-SVMs as a predictive tool in elevator traffic analysis. Discussion of Gaussian Fitting Results Figure 3 serves as a visual representation of the Gaussian fitting curves generated through MATLAB, offering insights into the temporal distribution of elevator traffic peaks observed over the course of a full daytime cycle.	cache/fcis-20728.pdf	txt/fcis-20728.txt