Session | ||
Advances in LCM through AI, data science & machine learning
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Presentations | ||
Expanding the Reach of Life Cycle Assessment with Artificial Intelligence Life Cycle Indonesia, Indonesia Stoichiometry-based prediction of life cycle inventories: Benchmarking & best practices 1Energy and Process Systems Engineering, ETH Zurich, Switzerland; 2Institute for Energy and Climate Research - Energy Systems Engineering (IEK-10), Forschungszentrum Jülich GmbH, Germany Environmental impact prediction of chemical processes using graph neural networks 1Process Intelligence Research, Department of Chemical Engineering, Delft University of Technology, Van der Maasweg 9, Delft 2629 HZ, The Netherlands; 2Pattern Recognition and Bioinformatics, Department of Intelligent Systems, Delft University of Technology, Van Mourik Broekmanweg 6, 2628 XE Delft, The Netherlands; 3CarbonMinds GmbH, Eupener Str. 165, 50933 Cologne, Germany A Novel Framework using Artificial Neural Networks to Predict Environmental Impacts of Construction Products 1Institute of Molecular Sciences, University of Bordeaux, Centre National de la Recherche Scientifique, Bordeaux INP, ISM, UMR 5255, 33400 Talence, France; 2Institute IWAR Material Flow Management and Resource Economy, Technical University Darmstadt, Germany; 3Data and AI Systems, Department of Computer Science, Technical University Darmstadt, Germany; 4WeLOOP, 254 Rue de Bourg, 59130 Lambersart, France Exploring the Potential of Word Vectorization for Automatic Prediction of Greenhouse Gas Emission Factor: Supervised Learning in Inventory Database for Environmental Analysis (IDEA) using word2vec The University of Tokyo, Japan |