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Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities
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Designing for Sustainability
eBook
Sofort lieferbar | Lieferzeit: Sofort lieferbar
Artikel-Nr:
9783030844592
Veröffentl:
2022
Einband:
eBook
Seiten:
235
Autor:
Panos M. Pardalos
Serie:
186, Springer Optimization and Its Applications
eBook Typ:
PDF
eBook Format:
Reflowable eBook
Kopierschutz:
Digital Watermark [Social-DRM]
Sprache:
Englisch
Beschreibung:
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.
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.
Cities as Convergent Autopoietic Systems (V. Dobrev).- Digital ‘Vitalism’ and its ‘Epistemic’ Predecessors: ‘Smart’ Neoteric History and Contemporary Approaches (Moraitis).- Unbuildable Cities (Th. Rassia).- Smart Cities as Identities (Tsoniotis).- A Cross-domain Landscape of ICT Services in Smart Cities (Bunhova).- A Novel Data Representation Method for Smart Cities’ Big Data (N. Nagy).- A Pedestrian Level Strategy to Minimize Outdoor Sunlight Exposure (X. Li).- Planning and Management of Charging Facilities for Electric Vehicle Sharing (W. Qi).- A Reactive Architectural Proposal for Fog/edge Computing in the Internet of Things Paradigm with Application in Deep Learning (Belmonte-Fernandez).- Urban Big Data: City Management and Real Estate Markets (Saiz).- Social Media-based Intelligence for Disaster Response and Management in Smart Cities (Khatoon).