The present study used artificial neural networks (ANNs) and experimental data to model the
viscosity of the MWCNT (50%)–Al 2 O 3 (50%)/10W40 hybrid nanofluid at different …

The two main challenges of predicting the wind speed depend on various atmospheric
factors and random variables. This paper explores the possibility of developing a wind …

The escalating levels of carbon dioxide (CO2) emissions represent the primary driver of
global warming, and addressing them is of paramount importance. Timely and accurate …

Text of abstract In the big data era, it is common to encounter data observed at different
frequencies. This raises the problem of how to explore the heterogeneous nonlinear …

ABSTRACT GDP is a measure of the size of the economy and how an economy is
performing. The mining industry has become a focal point in the total economic picture of …

Abstract Gross Domestic Product per capita is one of the most important indicators of social
welfare. All countries try to increase their Gross Domestic Product per capita to contribute to …

A traditional regression method involving time series variables is often observed at the same
frequencies. In a situation where the frequencies differ, the higher ones are averaged or …

[目的/意义] 随着机器学习算法研究的不断突破, 在GDP 预测领域中的应用也日益广泛.
系统梳理该领域的相关议题, 有助于学术研究的纵深发展.[方法/过程] 运用文献分析法对公开 …

Economic indicators are nowadays ones of the most observed, their development does not
only serve for comparing individual countries among each other but also show how the …

This study aims to use the random forest and extreme gradient boosting approaches to
forecast and analyse gross domestic product per capita using data from World Bank …