Abstract: This study aims to examine the relationship between energy usage and regional economic growth by employing multiple regression and random forest forecasting models. The results of this study ...
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 ...
ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...
Abstract: Measuring the equivalence ratio using flame spectral data is a key focus in combustion diagnostic techniques. Traditional methods rely on chemiluminescent bands with distinct spectral ...
Regression analysis is a powerful statistical method used to model relationships between variables. It's widely applied in various fields, from economics to machine learning. In this presentation, ...
State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Cancer Institute, Shanghai, China The high ...
The random forest regression (RFR) model was introduced to predict the multiple spin state charges of a heme model, which is important for the molecular dynamic simulation of the spin crossover ...
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