Pregled bibliografske jedinice broj: 1054429
Machine learning based system for managing energy efficiency of public sector as an approach towards smart cities
Machine learning based system for managing energy efficiency of public sector as an approach towards smart cities // International journal of information management, In Press (2020), 102074, 12 doi:10.1016/j.ijinfomgt.2020.102074 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1054429 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Machine learning based system for managing energy
efficiency of public sector as an approach
towards smart cities
Autori
Zekić-Sušac, Marijana ; Mitrović, Saša ; Has, Adela
Izvornik
International journal of information management (0268-4012) In Press
(2020);
102074, 12
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Planning models ; Energy efficiency ; Machine learning ; Public sector ; Smart cities
Sažetak
Energy efficiency of public sector is an important issue in the context of smart cities due to the fact that buildings are the largest energy consumers, especially public buildings such as educational, health, government and other public institutions that have a large usage frequency. However, recent developments of machine learning within Big Data environment have not been exploited enough in this domain. This paper aims to answer the question of how to incorporate Big Data platform and machine learning into an intelligent system for managing energy efficiency of public sector as a substantial part of the smart city concept. Deep neural networks, Rpart regression tree and Random forest with variable reduction procedures were used to create prediction models of specific energy consumption of Croatian public sector buildings. The most accurate model was produced by Random forest method, and a comparison of important predictors extracted by all three methods has been conducted. The models could be implemented in the suggested intelligent system named MERIDA which integrates Big Data collection and predictive models of energy consumption for each energy source in public buildings, and enables their synergy into a managing platform for improving energy efficiency of the public sector within Big Data environment. The paper also discusses technological requirements for developing such a platform that could be used by public administration to plan reconstruction measures of public buildings, to reduce energy consumption and cost, as well as to connect such smart public buildings as part of smart cities. Such digital transformation of energy management can increase energy efficiency of public administration, its higher quality of service and healthier environment.
Izvorni jezik
Engleski
Znanstvena područja
Ekonomija
POVEZANOST RADA
Projekti:
HRZZ-IP-2016-06-8350 - Metodološki okvir za učinkovito upravljanje energijom s pomoću inteligentne podatkovne analitike (MERIDA) (Zekić-Sušac, Marijana, HRZZ - 2016-06) ( CroRIS)
Ustanove:
Ekonomski fakultet, Osijek
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Social Science Citation Index (SSCI)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus