Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Machine Learning-Based Hourly Solar Irradiance Forecasting for Jimma City, Ethiopia: A Seasonal Performance Analysis

Domaine:

environment and energy

Type de record:

softwarepaper
Créateur:
Sem
Éditeur:
Zenodo
Hôte:avatar

Python scripts (preprocessing.py and modeling.py) for the paper titled 'Machine Learning-Based Hourly Solar Irradiance Forecasting for Jimma City, Ethiopia: A Seasonal Performance Analysis'. The scripts load NASA POWER hourly GHI data, perform feature engineering, train four machine learning models (Linear Regression, Random Forest, SVR, XGBoost), and generate all evaluation figures.

Visit

doi.org

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

Similaires

Advancing Very Short-Term Solar Irradiance Forecasting in Africa: a Low-Cost Sky Imaging and Machine Learning-Based ApproachModeling and Simulation of Hourly Irradiance for Solar Applications in Chad: Case of the City of AbecheSolar irradiance forecasting models using machine learning techniques and digital twin: A case study with comparisonMachine Learning‐Based Solar Photovoltaic Power Forecasting for Nigerian RegionsMachine Learning Based Diagnostic Comparative Modeling of Region-Specific Solar Irradiance in NigeriaShort-term and long-term solar irradiance forecasting with advanced machine learning techniques in Zafarana, Egypt

Advancing Very Short-Term Solar Irradiance Forecasting in Africa: a Low-Cost Sky Imaging and Machine Learning-Based Approach

Africa holds immense potential for solar energy, thanks to its high year-round solar irradiation. Ad

Modeling and Simulation of Hourly Irradiance for Solar Applications in Chad: Case of the City of Abeche

In this paper, the general objective is to model and simulate the hourly irradiance followed by an a

Solar irradiance forecasting models using machine learning techniques and digital twin: A case study with comparison

Machine Learning‐Based Solar Photovoltaic Power Forecasting for Nigerian Regions

ABSTRACT This study explores machine learning‐based forecasting of solar photovoltaic (PV) power ge

Machine Learning Based Diagnostic Comparative Modeling of Region-Specific Solar Irradiance in Nigeria

This study evaluates and compares the predictive performance of Multiple Linear Regression (MLR), Su

Short-term and long-term solar irradiance forecasting with advanced machine learning techniques in Zafarana, Egypt

Abstract The increasing demand for renewable energy sources has positioned solar