Druck auf Anfrage Neuware - Printed after ordering - This volume offers a wealth of interdisciplinary approaches to artificial intelligence, machine learning and optimization tools, which contribute to the optimization of urban features towards forming smart, sustainable, and livable future cities.Special features include:New research on the design of city elements and smart systems with respect to new technologies and scientific thinkingDiscussions on the theoretical background that lead to smart cities for the futureNew technologies and principles of research that can promote ideas of artificial intelligence and machine learning in optimized urban environmentsThe book engages students and researchers in the subjects of artificial intelligence, machine learning, and optimization tools in smart sustainable cities as eminent international experts contribute their research results and thinking in its chapters. Overall, its audience can benefit from a variety of disciplines including, architecture, engineering, physics, mathematics, computer science, and related fields.

Bestandsnummer des Verk�ufers 9783030844615

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Bibliografische Details

Titel: Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities : Designing for Sustainability
Verlag: Springer International Publishing, Springer Nature Switzerland
Ver�ffentlichungsdatum: 2023
Sprache: Englisch
ISBN-10: 3030844617
ISBN-13: 9783030844615
Bindung: Taschenbuch
Zustand: Neu

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Inhaltsangabe

This volume offers a wealth of interdisciplinary approaches to artificial intelligence, machine learning and optimization tools, which contribute to the optimization of urban features towards forming smart, sustainable, and livable future cities.

Special features include:

New research on the design of city elements and smart systems with respect to new technologies and scientific thinking
Discussions on the theoretical background that lead to smart cities for the future
New technologies and principles of research that can promote ideas of artificial intelligence and machine learning in optimized urban environments

The book engages students and researchers in the subjects of artificial intelligence, machine learning, and optimization tools in smart sustainable cities as eminent international experts contribute their research results and thinking in its chapters. Overall, its audience can benefit from a variety of disciplines including, architecture, engineering, physics, mathematics, computer science, and related fields.

�ber die Autorin bzw. den Autor

Panos M. Pardalos serves as distinguished professor of industrial and systems engineering at the University of Florida. Additionally, he is the Paul and Heidi Brown Preeminent Professor of industrial and systems engineering. Professor Pardalos is also an affiliated faculty member of the computer and information science department, the Hellenic Studies Center, and the biomedical engineering program. Additionally, he serves as the director of the Center for Applied Optimization. Professor Pardalos is a world leading expert in global and combinatorial optimization. His recent research interests include network design problems, optimization in telecommunications, ecommerce, data mining, biomedical applications, and massive computing. Panos Pardalos is a prolific author who lectures all over the world. He is the recipient of a multitude of fellowships and awards, the most recent of which is the Humboldt Research Award (2018).

Stamatina Th. Rassia is an architect engineer holding a diploma in Architecture Engineering from the National Technical University of Athens (NTUA) in Greece. She has an MPhil in Environmental Design in Architecture and a PhD in Architecture from the University of Cambridge in the United Kingdom. Dr. Rassia is an expert on topics of sustainability and public health promotion by architectural design.

Arsenios Tsokas holds a BSc in Mathematics from the Aristotle University of Thessaloniki in Greece and a PhD in Industrial & Systems Engineering from the University of Florida in USA. He has a diverse background including data analysis, optimization, and machine learning.

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