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 …

Data preprocessing is a crucial step for mining and learning from data, and one of its primary
activities is the transformation of data. This activity is very important in the context of time …

Crude oil is one of the most important types of energy for the global economy, and hence it is
very attractive to understand the movement of crude oil prices. However, the sequences of …

With the popularity of the deep learning model in the engineering fields, it has attracted
significant research interests in the economic and finance fields. In this paper, we use the …

As the supply of commodities forms essential lifelines for modern society, commodity price
fluctuations can significantly impact the operation and sustainable development of …

Current existing literatures can characterize the long-term fluctuation of crude oil price time
series, however, it is difficult to detect the fluctuation mechanism specifically under short …

The rapid increase in urbanization has resulted in a significant rise in electricity
consumption, which resulted in a wide gap between the amount of electricity generated and …

Forecasting electricity consumption can help policymakers to properly plan for economic
development. This is possible through energy conservation by avoiding excessive …

As one of the leading types of energy, crude oil plays a crucial role in the global economy.
Understanding the movement of crude oil prices is very attractive for producers, consumers …

Multiple factors affect crude oil price including economic cycle, international relations,
geopolitics etc. Forecasting oil price is a challenging but rewarding task. In this study, we …