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Automation Days 2025 - Presentation at Session S1-A: Energy systems, green transition

Year: 2025

Type: article

Abstract: Presentation sharing some scientific insight on interpretable machine learning to automation professionals participating to The Automation Days 2025, Smart, safe and secure automation. FUELGAE project was presented as one case study, explaining about dealing with a prediction of biocrude yield with less complex, explainable models. https://www.automaatioseura.fi/automationdays2025/

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.18182616

Author: Ohenoja, Markku

Institution: University of Oulu

Language: English

Topic: Explainable Artificial Intelligence (XAI)

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: European Commission

Award: Sustainable On-site and Innovative Technologies for Advanced Transport BioFuels from MιcroalGae