Buch, Englisch, Band 637, 215 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 518 g
Reihe: IFIP Advances in Information and Communication Technology
9th IFIP WG 12.6 and 1st IFIP WG 12.11 International Workshop, AI4KMES 2021, Held at IJCAI 2021, Montreal, QC, Canada, August 19¿20, 2021, Revised Selected Papers
Buch, Englisch, Band 637, 215 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 518 g
Reihe: IFIP Advances in Information and Communication Technology
ISBN: 978-3-030-96591-4
Verlag: Springer International Publishing
The 15 papers included in this book were carefully reviewed and selected from 17 submissions. They deal with knowledge management and sustainability challenges, focusing on methodological, technical and organizational aspects of AI used for facing related complex problems. This year's topic was AI for Knowledge Management, Energy and Sustainable Future.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Greening and Smarting IT – Case of Digital Transformation.- Crowdsourcing and Sharing Economy in the Smart City Concept. Influence of the Idea on Development and Urban Resources.- Assessment of Smart Waste Management Systems with Spherical AHP Method.- Zero Carbon Energy Transition in the Kitchen.- Barriers and Challenges of Knowledge Management in a Gas Company.- Characterization of residential electricity customers via Deep Ensemble Learning.- Grid Imbalance Prediction Using Particle Swarm Optimization and Neural Networks.- Collective Intelligence of Honey Bees for Energy and Sustainability.- The Application of Artificial Intelligence to Nuclear Power Plants Safety.- Capacity to build Artificial Intelligence Systems for Nuclear Energy Security and Sustainability: Experience of Belarus.- Automated Planning to Evolve Smart Grids with Renewable Energy.- Artificial Intelligence Application for Crude Distillation Unit: An overview.- Deep Reinforced Learning for the Governance of a SampleMicrogrid.- Residential Short-Term Load Forecasting via Meta Learning and Domain Augmentation.- Renewable Energy Investment Decision Evaluation for Local Authorities.