Abstract: Since the deregulation of the power markets, accurate short term Electricity Price Forecasting (EPF) has become crucial in maximizing economic benefits and mitigating power market risks. Due ...

This repository contains all scripts, notebooks, figures, and data workflows used to reproduce the study: A. Al Nafees, M. Hassan, A. Paul, S. S. Shraban and H. Deb Mahin, "Public Transport Ridership ...

Abstract: The accuracy of rainfall prediction in Nigeria is significantly enhanced through the application of machine learning models. This study employs a comprehensive approach that integrates ...

Machine-Learning-Model-for-Weather-Forecasting Purpose of this project is to predict the temperature using different algorithms like linear regression, random forest regression, and Decision tree ...

ISLAMABAD: The Federal Board of Revenue (FBR) has applied the buoyancy-based forecasting framework to estimate the tax collections for 2026-27. According to a FBR report on tax estimates for 2026-27 ...

David Gerbing from the School of Business at Portland State University introduces lessR, a tool designed to facilitate professional-quality data visualizations and data analysis without programming re ...

It feels like there’s no escaping AI right now, whether you’re trying to type a sentence without being interrupted by a digital “assistant” or struggling to find a new refrigerator that doesn’t ...

Thomas J Catalano is a CFP and Registered Investment Adviser with the state of South Carolina, where he launched his own financial advisory firm in 2018. Thomas' experience gives him expertise in a ...

AAA projects historic Florida holiday travel crowds despite higher costs at the pump, driven by resilient consumer vacation ...

Enhancing PM2.5 Forecasting in arid urban environments Using Deep Learning Models: A multi-station analysis from the UAE Siva Durga Adduri Hana Sulieman Fatin Samara Firuz Kamalov Frontiers in ...