id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ajst-31456	Jiang, Wenyu	Prediction of Demand for Shared Bicycles Based on Machine Learning	2025	10	.pdf	application/pdf	6972	340	47	Finally, many models are constructed for evaluation and comparison, and it is found that the tree based model LightGBM has the best effect. [8] discussed the main influencing factors of short-term (hour based) demand forecasting for shared bicycles based on the multi-dimensional large sample data of shared bicycles, using machine learning models such as lasso regression, ridge regression, random forest and iterative decision tree, and compared the forecasting effects of different models.	cache/ajst-31456.pdf	txt/ajst-31456.txt