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 ...

Abstract: Random Forest is a well-known type of ensemble learning, which combines a number of decision trees to improve the prediction ability and reduce the risk of overfitting. This paper aims at ...

What happened: A big new global study just dropped, and it shows that AI has pretty much taken over the world of academic research. Why this is important: But here’s the interesting twist: most ...

Medical research plays a vital role in advancing healthcare, improving treatment, and informing public health policies. However, it can be difficult to understand a study or whether it is trustworthy.

ABSTRACT: Biogas is gaining prominence as a renewable energy source with significant potential to reduce greenhouse gas emissions and mitigate environmental impacts associated with fossil fuels. This ...

1 Department of Neurology, Hubei No. 3 People’s Hospital of Jianghan University, Wuhan, China 2 Support Centre, Hubei No. 3 People’s Hospital of Jianghan University, Wuhan, China Background and aim: ...

ABSTRACT: Road traffic accidents are one of the global safety and socioeconomic challenges. According to WHO (2024), it has caused over 1.19 million annual fatalities. It is also projected to cause ...

The operation of the power grid is closely related to meteorological disasters. Changes in meteorological conditions may have an impact on the operation and stability of the power system, leading to ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random forest regression technique (and a variant called bagging regression), where the goal is to ...

A machine learning random forest regression system predicts a single numeric value. A random forest is an ensemble (collection) of simple decision tree regressors that have been trained on different ...