This paper is focused on the concise review of the specific applications of genetic algorithms
in forecasting commodity prices. Genetic algorithms seem relevant in this field for many …

In this article, we provide a structured review of crude oil price dynamics. Specifically, we
summarize evidence on important factors determining oil prices, cover the impact of oil …

As crude oil price is influenced by numerous factors, capturing its behavior precisely is quite
challenging, and thus leads to the difficulty of forecasting. In this study, a deep learning …

In recent years, the crude oil market has entered a new period of development and the core
influence factors of crude oil have also been a change. Thus, we develop a new research …

The prediction of crude oil prices has important research significance. The paper contributes
to the literature of hybrid models for forecasting crude oil prices. We apply ensemble …

In this paper, an improved slope-based method (ISBM) based on empirical mode
decomposition (EMD) and feed-forward neural network (FNN) method, namely, the EMD …

Forecasting the price of crude oil is a challenging task. To improve this forecasting, this
paper proposes a novel hybrid method that uses an integrated data fluctuation network …

Crude oil is one of the most important trade commodities in the world and its price fluctuation
has significant effects on global economic activities. In this paper, we proposed hybrid …

Channel state information (CSI) estimation is part of the most fundamental problems in 5G
wireless communication systems. In mobile scenarios, outdated CSI will have a serious …

This paper sets out to investigate the predictive power of investor attention onto oil prices.
We firstly construct investor attention index by using the Google search volume index (SVI) …