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Titlebook: Computational Intelligence Techniques for Green Smart Cities; Mohamed Lahby,Ala Al-Fuqaha,Yassine Maleh Book 2022 The Editor(s) (if applic

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发表于 2025-3-21 18:14:44 | 显示全部楼层 |阅读模式
书目名称Computational Intelligence Techniques for Green Smart Cities
编辑Mohamed Lahby,Ala Al-Fuqaha,Yassine Maleh
视频video
概述Proposes the latest discoveries of machine intelligence techniques and methods for green smart cities.Presents high-quality and original research on computational intelligence for green smart cities r
丛书名称Green Energy and Technology
图书封面Titlebook: Computational Intelligence Techniques for Green Smart Cities;  Mohamed Lahby,Ala Al-Fuqaha,Yassine Maleh Book 2022 The Editor(s) (if applic
描述.This book contains high-quality and original research on computational intelligence for green smart cities research. In recent years, the use of smart city technology has rapidly increased through the successful development and deployment of Internet of Things (IoT) architectures. The citizens‘ quality of life has been improved in several sensitive areas of the city, such as transportation, buildings, health care, education, environment, and security, thanks to these technological advances.Computational intelligence techniques and algorithms enable a computational analysis of enormous data sets to reveal patterns that recur. This information is used to inform and improve decision-making at the municipal level to build smart computational intelligence techniques and sustainable cities for their citizens. Machine intelligence allows us to identify trends (patterns). The smart city could better integrate its transportation network, for example. By offering a better public transportation network adapted to the demand, we could reduce personal vehicles and energy consumption. A smart city could use models to predict the consequences of a change, such as pedestrianizing a street or addi
出版日期Book 2022
关键词Computational Intelligence; Artificial Intelligence; Machine Learning; Green smart city; Green IoT; Green
版次1
doihttps://doi.org/10.1007/978-3-030-96429-0
isbn_softcover978-3-030-96431-3
isbn_ebook978-3-030-96429-0Series ISSN 1865-3529 Series E-ISSN 1865-3537
issn_series 1865-3529
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Mohamed Lahby,Ala Al-Fuqaha,Yassine MalehProposes the latest discoveries of machine intelligence techniques and methods for green smart cities.Presents high-quality and original research on computational intelligence for green smart cities r
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Green Energy and Technologyhttp://image.papertrans.cn/c/image/232408.jpg
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But What is the Driving Mechanism?,logies for building green smart cities. These new forms of energy can complete the world’s energy demand, protect the environment and provide energy security. Statistics have shown that renewable energy resources offer between 15 and 30% of the world’s energy. Moreover, the production and consumptio
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Friedrich Wilhelm Bessel: 61 Cygni of sources, such as smart metres, sensors and other devices. Machine learning encompasses several techniques to process and visualise data. Each technique is specifically suited to certain data types and problems, whether it be supervised, unsupervised or reinforcement learning. These techniques ca
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https://doi.org/10.1007/978-3-030-80309-4green transportation performance evaluation using the Balanced Scorecard. We propose a set of indicators to evaluate green transportation. These indicators are selected based on Fuzzy-Delphi method following different quantitative judgments of experts. The various criteria are related to the green t
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Politik und Gesellschaft des Nahen Ostensn smart city intelligence and safety to fight against the COVID-19 pandemic. For this, we have realized a model that allows transporting citizens via a means of transportation based on electric mobility to reduce energy consumption, reduce CO. emission and cost by searching the optimal path that thi
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