In today's context of escalating environmental pressure, traditional methods of natural resource conservation face numerous challenges. The use of big data analytics to support the formulation of environmental policies has become a crucial approach for enhancing the efficiency and scientific...

Online health consultation services are crucial for mental health support, particularly in densely populated areas. However, the heavy reliance on human expertise often leads to delays, necessitating more efficient and automated solutions. This study developed a machine learning framework to...

Purpose The proposed model has been aimed to predict stock market signals by designing an accurate model. In this sense, the stock market is analysed by the technical analysis of Japanese Candlestick, which is combined by the following meta heuristic algorithms: support vector machine (SVM),...

This study investigates the effect of Nigeria's population on four selected banking transaction channels. The Nigerian projected population (2022-2027) was used as an input variable for forecasting future volumes of transactions for each channel. The results show that the Support Vector...

In this study, we proposed two types of hybrid models based on the heterogeneous autoregressive (HAR) model and support vector regression (SVR) model to forecast realized volatility (RV). The first model is a residual-type model, where the RV is first predicted using the HAR model, and the...