Abstract: The research introduces a methodology to predict the flexural behavior of a laminate before conducting any experimental tests. To derive such a model, an artificial intelligence (AI)-based ...
Abstract: Predicting volatile commodity prices is challenging due to frequent outliers, which compromise traditional models like Random Forest (RF) that rely on Mean ...
A Python implementation of the Truly Spatial Random Forests (SRF) algorithm for geoscience data analysis. Based on: Talebi, H., Peeters, L.J.M., Otto, A. & Tolosana-Delgado, R. (2022). A Truly Spatial ...
Researchers from Japan's Waseda University have developed a new model that optimizes the route of electric delivery vehicles (EDVs) to maximize local PV surplus usage. For this purpose, the academics ...
ABSTRACT: An integrated model approaching to combining the BETR-GLOBAL model with a Random Forest method was developed in this research. Firstly, the BETR-GLOBAL model was employed to simulate the ...
Design and Implementation of Random Forest algorithm from scratch to execute Pacman strategies and actions in a deterministic, fully observable Pacman Environment. This is a Machine Learning model ...
ABSTRACT: The aim of this study is to establish the estimation model of potassium content in apple leaves by using vegetation index. A total of 96 fresh apple leaves were collected from 24 orchards in ...
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