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Titlebook: Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities; Designing for Sustai Panos M. Pardalos,Stamatina Th. Ra

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期刊全称Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities
期刊简称Designing for Sustai
影响因子2023Panos M. Pardalos,Stamatina Th. Rassia,Arsenios Ts
视频video
发行地址Combines interdisciplinary expertise in the subject matter.Offers a platform on multivariate information presented.Presents concepts, research results, ideas and methods to explore a more complete pic
学科分类Springer Optimization and Its Applications
图书封面Titlebook: Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities; Designing for Sustai Panos M. Pardalos,Stamatina Th. Ra
影响因子.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..
Pindex Book 2022
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Analysis of Software Product Linest. Such correlations could probably be detected, between the contemporary “smart” approaches of the topology oriented design references or present-day digital technology and the scientific and cultural interest of the nineteenth century, the latter focusing on change, movement, and evolution. We cou
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https://doi.org/10.1007/978-3-642-77193-4ows to express a multivariate time series with one sequence of symbols. Integrating individual sequences in one symbolic sequence provides better expressive power, while our modified SAX distance measure can be applied for clustering and classification tasks in smart cities, decreasing the enormous
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https://doi.org/10.1007/978-3-642-77193-4makers in the format most appropriate for carrying out emergency response and coordination efficiently. We developed a dashboard-like interface to facilitate such goal..For any disaster or emergency, the heterogeneous nature (texts, image, audio, and videos) and sheer volume of data instantly availa
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1931-6828 ults 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..978-3-030-84461-5978-3-030-84459-2Series ISSN 1931-6828 Series E-ISSN 1931-6836
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Artificial Intelligence, Machine Learning, and Optimization Tools for Smart CitiesDesigning for Sustai
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