Disruptive Information Technologies for a Smart Society (eBook, PDF)

Proceedings of the 14th International Conference on Information Society and Technology (ICIST)
Redaktion: Trajanovic, Miroslav; Zdravkovic, Milan; Filipovic, Nenad

• Format: PDF

Produktbeschreibung

This book aims at meeting the challenge of getting along with today's unprecedented rate of innovation supported by disruptive digital technologies, which changed the perception of the productivity and effectiveness and opened a gateway to more than ever dynamic advances in solving the important societal challenges.

"Disruptive Information Technologies for a Smart Society" is the proceedings book of the 14th International Conference for Information Society and Technologies that brings together experts from various fields to discuss the latest advancements in industrial AI, digitalization in health, well-being and sport, enterprise information systems, large language models, and security and safety.

The book and the conference serve as a platform for researchers of all career stages in technical sciences, especially Ph.D. students, practitioners, and industry experts in health care, AI and other areas to share and learn on the cutting-edge technologies and stay at the forefront of these rapidly evolving fields.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 438
• Erscheinungstermin: 29. September 2024
• Englisch
• ISBN-13: 9783031714191
• Artikelnr.: 71804247

Inhaltsangabe

Machine Learning Model for Prediction of Indicative Water Parameters on the Danube River based on Satellite Data.- XGBoost is all you need the case of forecasting transmitted heat energy in District Heating Systems.- XAI4HEAT Towards demand-driven, AI facilitated, end-to-end management of District Heating Systems.- integrated Multi Criteria Decision Analysis Sizing Optimization and Demand Side Management for Defining Optimal System Configuration while Reducing Costs and CO2 Emissions.