Pregled bibliografske jedinice broj: 977715
Searching for an Optimal Partition of Incomplete Data with Application in Modeling Energy Efficiency of Public Buildings
Searching for an Optimal Partition of Incomplete Data with Application in Modeling Energy Efficiency of Public Buildings // Croatian operational research review, 9 (2018), 2; 255-268 doi:10.17535/crorr.2018.0020 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 977715 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Searching for an Optimal Partition of Incomplete Data with Application in Modeling Energy Efficiency of Public Buildings
Autori
Scitovski, Rudolf ; Zekić Sušac, Marijana ; Has, Adela
Izvornik
Croatian operational research review (1848-0225) 9
(2018), 2;
255-268
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
clustering ; incomplete data ; missing data ; optimal partition ; energy efficiency of public buildings
Sažetak
In this paper, we consider the problem of searching for an optimal partition with the most appropriate number of clusters for an incomplete data set in which several outliers might occur. Special attention is given to the application of the Least Squares distance-like function. The procedure of preparing the incomplete data set and the outlier elimination procedure are proposed such that the clustering process gives acceptable solutions. Appropriate justifications with proof are provided for these procedures. An incremental algorithm for searching for optimal partitions with 2, 3, ... clusters is applied on the prepared data set. After that, by using the Davies-Bouldin and the Calinski Harabasz index the most appropriate number of clusters is determined. The whole procedure is organized as an algorithm given in the paper. In order to illustrate its applicability, the above steps are applied on the real data set of public buildings and their energy efficiency data, providing clear clusters that could be used for further modeling procedures.
Izvorni jezik
Engleski
POVEZANOST RADA
Projekti:
HRZZ-IP-2016-06-6545 - Optimizacijski i statistički modeli i metode prepoznavanja svojstava skupova podataka izmjerenih s pogreškama (OSMoMeSIP) (OSMoMeSIP) (Scitovski, Rudolf, HRZZ ) ( CroRIS)
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,
Sveučilište u Osijeku, Odjel za matematiku
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Emerging Sources Citation Index (ESCI)
- Scopus
- EconLit
Uključenost u ostale bibliografske baze podataka::
- INSPEC
- MathSciNet
- CompactMath: Current Index to Statistics
- Current Mathematical Publications
- DOAJ: Genamics Journal Seek database
- HRČAK
- ProQuest