An Improved and Explainable Electricity Price Forecasting Model via SHAP-Based Error Compensation Approach

Engineering, Energy Engineering, Information Science, Electronic Information, Artificial Intelligence,
electricity price forecasting   explainable artificial intelligence   SHAP method   error compensation   neural networks   electricity markets   price volatility  

Improved Electricity Price Forecasting Model Based on SHAP and Its Explainability Analysis Background and Research Motivation Electricity price forecasting (EPF) models have become a hot research topic in recent years, particularly due to the financial impact of market volatility on stakeholders. Especially in European energy markets, recent years ...

Empowering Glioma Prognosis with Transparent Machine Learning and Interpretative Insights Using Explainable AI

Information Science, Computer Science, Artificial Intelligence, Medicine, Basic Medical Sciences, Neurology, Oncology,
glioma   molecular makeup   explainable artificial intelligence   SHAP   LIME   Qlattice   ELI5   machine learning  

Enabling Explainable Artificial Intelligence for Glioma Prognosis: Translational Insights from Transparent Machine Learning Academic Background This study is dedicated to developing a reliable technique to detect whether patients have a specific type of brain tumor—glioma—using various machine learning methods and deep learning methods, combined wi...