Übersicht			Auf mobile öffnen

Lieferstatus:	Vorankündigung
Veröffentlichung:	ANGEKÜNDIGT (Juli 2026)
Genre:	Naturwissensch., Medizin, Technik
	Applied Dynamical Systems / Big Data / Controls / Data Analysis and Big Data / data assimilation / Data Fusion / Datenbanken / DDDAS / Digital Twins / Electronics and Microelectronics, Instrumentation / Elektronik / High Performance Computing / Instrumentation / Kybernetik und Systemtheorie / machine learning / Special Purpose and Application-Based Systems / Statistical Modeling / Systems Theory, Control / Wissensbasierte Systeme, Expertensysteme mehr...
ISBN:	9783031885730
EAN-Code:	9783031885730
Verlag:	Springer International Publishing
Einband:	Gebunden
Sprache:	English
Dimensionen:	H 235 mm / B 155 mm / D
Seiten:	970
Illustration:	XII, 970 p. 152 illus., 136 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Keine Bewertung vor Veröffentlichung möglich.

Inhalt:

This authoritative reference on the Dynamic Data Driven Applications Systems paradigm benefits science and technology researchers and practitioners developing DDDAS-based technologies. This Third Volume in the handbook series offers 35 chapters contributed by leading experts, organized in nine thematic areas spanning natural, engineered, or societal systems to enable an accurate understanding, analysis, and control of corresponding complex systems.  The work presented shows how DDDAS unifies the computational and instrumentation aspects of an application system, extends computing notions to span from the high-end to edge computing and real-time data acquisition and control, adaptively manages the operation of complex, distributed, multimodal systems through high-dimensional, systems-cognizant model-coordination and multi-objective optimization of resources and service delivery; supports methodologies for achieving autonomic and enhanced AI capabilities; and provides a foundational concept for Predictive Digital Twins and Dynamic Digital Twins. Advance Praise: DDDAS opened the way to combine real-time data sensing with simulation modeling, thereby creating a way to produce fast predictions with unprecedented accuracy. The adoption of the technique has impacted a broad spectrum of applications.  The March 2023 US National Academies (NASEM) Report on "Foundational Research Gaps and Future Directions for Digital Twins" identifies DDDAS as an early concept that "has all of the elements of a digital twin, including the physical, the virtual, and the two-way interaction via a feedback loop".  The Report also characterizes Digital Twins as holding "immense promise in accelerating scientific discovery and revolutionizing industries."  The chapters in this volume give insight to that cited power of Digital Twins through the accomplishments reported for DDDAS, allowing S&T experts to dig deeply in specific areas, as well as providing hints for new ways to deploy it.   ­                                                                                                                                                         -Harold Stone, Ph.D. (Fellow Emeritus, NEC Research Institute) The development of trusted Dynamic Data-Driven Applications Systems will enable leaps forward in scientific discovery, from autonomous robotic exploration of planetary surfaces to unprecedented skill in weather and climate prediction. But the applications will go well beyond academia: digital twins, enabled by DDDAS, will help describe the interaction of humans with the environment and will be critical tools for policymakers and urban planners.                                                                                       -Michael Seablom (Associate Director for Technology in the Earth Science Division and Head of the Earth                                                                                                               Science Technology Office (ESTO), NASA Headquarters)