Resource management is addressed using infrastructure as a service. On demand, the
resource management module effectively manages available resources. Resource …

The core objective of this work is to predict stock market indices' using autoregressive
integrated moving average (ARIMA), artificial neural network (ANN) and their combination in …

Given the numerous factors that can influence stock prices such as a company's financial
health, economic conditions, and the political climate, predicting stock prices can be quite …

This study investigates the utilization of artificial intelligence (AI) for feature engineering in
the education sector, highlighting its potential to enhance individualized learning and …

Financial engineering is crucial for effectively combining finance with quantitative
approaches. This study aims to forecast the performance of the Nasdaq stock market by …

Emotion prediction is crucial in areas such as human–computer interaction, consumer
experience, and mental health treatment; nonetheless, effectively forecasting emotions is …

PM2. 5 is a significant factor in the troubling air quality that presently affects many countries
globally. Therefore, dependable prediction models are needed for the government to enable …

This study researches the forecasting accuracy of Interest Rate Swap Spreads (IRSS) us-ing
both econometric models and machine learning techniques, with a focus on integrating …

This study explored the complexities of modeling and forecasting inflation rates in Kenya,
leveraging a sophisticated ARIMA-ANN hybrid model. Traditional ARIMA models, although …

Gold is one of the most valuable metals in the world with numerous applications, including
jewelry and electronic devices. Countries often utilize gold as an economic health indicator …