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010 a| 2024006963;

020 a| 9781394172061q| (paperback);

020 z| 9781394172085q| (adobe pdf);

020 z| 9781394172078q| (epub);

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050 00 a| TA347.A78b| A85 2024;

082 00 a| 620/.00420285632| 23/eng/20240314;

245 00 a| Artificial intelligence in performance-driven designh| [electronic resource] :b| theories, methods, and tools /c| edited by Narjes Abbasabadi, University of Washington, Seattle, USA, Mehdi Ashayeri, Southern Illinois University Carbondale, Carbondale, USA.;

250 a| First edition.;

260 a| Hoboken, New Jersey :b| Wiley,c| [2024];

263 a| 2405;

300 a| pages cm;

504 a| Includes bibliographical references and index.;

506 a| Available only to authorized users.;

520 a| "The recent advances in data-driven approaches and big data initiatives provide enormous opportunities for sustainable design and research in decarbonization and digital transformation of the built environment. The Artificial Intelligence and Sustainable Design: Theories, Methods, and Tools book aims to comprehensively review the application of Artificial Intelligence (AI), particularly Machine Learning (ML), in enhancing performance-based design and offer advanced insight into different approaches, methods, and tools for bringing the power of AI in simulation platforms and leveraging digital twin throughout the life cycle of the built environment. The contents center on fundamentals of building science, including key performance indicators such as comfort, indoor/outdoor environmental quality, solar and daylight, and energy exploring human-centered and evidence-based design and optimization procedures and integrating intelligent systems for better understanding, designing, and managing our existing and future built environments"--c| Provided by publisher.;

538 a| Mode of access: World Wide Web;

650 0 a| Artificial intelligencex| Industrial applications.=| ^A15394;

650 0 a| Engineering designx| Data processing.=| ^A116294;

655 0 a| Electronic books.=| ^A491897;

700 1 a| Abbasabadi, Narjes.?| UNAUTHORIZED;

700 1 a| Ashayeri, Mehdi.?| UNAUTHORIZED;

856 40 z| Full text available from eBooks on EBSCOhostu| https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=3878642&scope=site&custid=s5822723&authtype=ip,shib;

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999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 6741930-3001l| MNETm| JMUSICr| Ys| Yt| MNESSBKu| 7/15/2026x| EBOOKz| JERESOURCE;

Artificial intelligence in performance-driven design theories, methods, and tools / edited by Narjes Abbasabadi, University of Washington, Seattle, USA, Mehdi Ashayeri, Southern Illinois University Carbondale, Carbondale, USA.

Other author	Abbasabadi, Narjes.
Other author	Ashayeri, Mehdi.
Format	Electronic
Edition	First edition.
Publication Info	Hoboken, New Jersey : Wiley, [2024]
Description	pages cm
Supplemental Content	Full text available from eBooks on EBSCOhost
Subjects	Artificial intelligence--Industrial applications. Engineering design--Data processing.

Abstract	"The recent advances in data-driven approaches and big data initiatives provide enormous opportunities for sustainable design and research in decarbonization and digital transformation of the built environment. The Artificial Intelligence and Sustainable Design: Theories, Methods, and Tools book aims to comprehensively review the application of Artificial Intelligence (AI), particularly Machine Learning (ML), in enhancing performance-based design and offer advanced insight into different approaches, methods, and tools for bringing the power of AI in simulation platforms and leveraging digital twin throughout the life cycle of the built environment. The contents center on fundamentals of building science, including key performance indicators such as comfort, indoor/outdoor environmental quality, solar and daylight, and energy exploring human-centered and evidence-based design and optimization procedures and integrating intelligent systems for better understanding, designing, and managing our existing and future built environments"-- Provided by publisher.
Bibliography note	Includes bibliographical references and index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Genre/form	Electronic books.
LCCN	2024006963
ISBN	9781394172061 (paperback)
ISBN	(adobe pdf)
ISBN	(epub)

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Artificial intelligence in performance-driven design theories, methods, and tools / edited by Narjes Abbasabadi, University of Washington, Seattle, USA, Mehdi Ashayeri, Southern Illinois University Carbondale, Carbondale, USA.

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