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Guest Editorial: Special Issue on Computational Intelligence for Smart Energy Applications to Smart Cities
Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan.
Department of Engineering Durham University Durham, U.K.
Department of Computer Science University of Exeter, Innovation Center, Exeter, U.K.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-1902-9877
2019 (English)In: IEEE Transactions on Emerging Topics in Computational Intelligence, E-ISSN 2471-285X, Vol. 3, no 3, p. 173-176Article in journal, Editorial material (Other academic) Published
Abstract [en]

The papers in this special section focus on computational intelligence for smart energy applications in smart cities. By 2050, more than half the world’s population is expected to live in urban regions. This rapid expansion of population in the cities of the future will lead to increasing demands on various infrastructures; the urban economics will play a major role in national economics. Cities must be competitive by providing smart functions to support high quality of life. There is thus an urgent need to develop smart cities that possess a number of smart components. Among them, smart energy is arguably the first infrastructure to be established because almost all systems require energy to operate. Smart energy refers to energy monitoring, prediction, use or management in a smart way. In smart cities, smart energy applications include smart grids, smart mobility, and smart communications. While realizing smart energy is promising to smart cities, it involves a number of challenges. The articles in this section aim to provide in-depth CI technologies that enable smart energy applications to smart cities.

Place, publisher, year, edition, pages
IEEE, 2019. Vol. 3, no 3, p. 173-176
National Category
Media and Communication Technology
Research subject
Pervasive Mobile Computing
Identifiers
URN: urn:nbn:se:ltu:diva-76289DOI: 10.1109/TETCI.2019.2911783ISI: 000681781000001Scopus ID: 2-s2.0-85082634278OAI: oai:DiVA.org:ltu-76289DiVA, id: diva2:1358781
Available from: 2019-10-08 Created: 2019-10-08 Last updated: 2021-12-13Bibliographically approved

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Vasilakos, Athanasios

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