Guest Editorial

Special Issue on Computational Intelligence for Smart Energy Applications to Smart Cities

Document identifier:
Access full text here:10.1109/TETCI.2019.2911783
Keyword: Natural Sciences, Computer and Information Sciences, Media and Communication Technology, Naturvetenskap, Data- och informationsvetenskap, Medieteknik, Pervasive Mobile Computing, Distribuerade datorsystem
Publication year: 2019
Relevant Sustainable Development Goals (SDGs):
SDG 7 Affordable and clean energySDG 11 Sustainable cities and communitiesSDG 12 Responsible consumption and production
The SDG label(s) above have been assigned by


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.


Wei-Yu Chiu

Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan
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Hongjian Sun

Department of Engineering Durham University Durham, U.K
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Chao Wang

Department of Computer Science University of Exeter, Innovation Center, Exeter, U.K
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Athanasios Vasilakos

Luleå tekniska universitet; Datavetenskap
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