Abstract: This study proposes a multivariate dynamic cost standard prediction model based on random forest; LSTM is combined with XGBoost to solve the problem of accuracy in predicting complex cost ...

The Forest Pavilion at COP30 embodies a shared global commitment to forests as a cornerstone of climate action, biodiversity conservation, and sustainable development. It serves as an inclusive, multi ...

Abstract: This study explores the use of Random Forest, a versatile machine learning algorithm, for predicting wine quality. By creating multiple decision trees and combining their predictions, Random ...

Background: Decisions surrounding involuntary psychiatric treatment orders often involve complex clinical, legal, and ethical considerations, especially when patients lack decisional capacity and ...

EV Sales Prediction in India using Machine Learning. Forecasts electric vehicle sales across Indian states with interactive visualizations and a modern web UI.

In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat 8 remote ...

College of Mathematical and Statistics, Sichuan University of Science and Engineering, Zigong, China. With the rapid development of the global economy and the acceleration of urbanization, ...