5 papers
Forecasting solar power output in Ibadan: A machine learning approach leveraging weather data and system specifications
Obarotu Peter Urhuerhi, Christopher Udomboso, Caston Sigauke
This study predicts hourly solar irradiance components, Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI), and Diffuse Horizontal Irradiance (DHI) using meteorolog…
Fusion Sampling Validation in Data Partitioning for Machine Learning
Christopher Godwin Udomboso, Caston Sigauke, Ini Adinya
Effective data partitioning is known to be crucial in machine learning. Traditional cross-validation methods like K-Fold Cross-Validation (KFCV) enhance model robustness but often…
A Comparative Modelling of Essential Characteristics of Volatility: Simulation and Empirical Study
Richard T. A. Samuel, Charles Chimedza, Caston Sigauke
This study utilised the dynamics of five time-varying models to estimate six essential features of financial return volatility that are relevant for robust risk management. These f…
Robust modelling framework for short-term forecasting of global horizontal irradiance
Edina Chandiwana, Caston Sigauke, Alphonce Bere
The increasing demand for electricity and the need for clean energy sources have increased solar energy use. Accurate forecasts of solar energy are required for easy management of…
Asymptotic dependence modelling of the BRICS stock markets
Caston Sigauke, Rosinah Mukhodobwane, Wilbert Chagwiza +1
With the use of empirical data, this paper focuses on solving financial and investment issues involving extremal dependence of ten pairwise combinations of the five BRICS (Brazil,…