Abstract Machine learning methods have been adopted in the literature as contenders to
conventional methods to solve the energy time series forecasting (TSF) problems. Recently …

Addressing the issue of shrinking saline lakes around the globe has turned into one of the
most pressing issues for sustainable water resource management. While it has been …

The principal objective of this article is to examine, compare, and develop a time series
model for forecasting the growth of the life insurance business in Thailand. The proposed …

Cryptocurrencies are increasing in importance. While to start with they were used only in
virtual reality platforms for games, nowadays they are being used by many institutions and …

The primary aim of this article is to investigate, contrast, and formulate a time series model to
predict Bangkok's overall population. In this study, we intend to propose a hybrid model that …

The aim of the study is to evaluate two commonly used time series methods for forecasting
Bitcoin (BTC) prices: the Autoregressive Integrated Moving Average (ARIMA) and the …