case study in maintenance cost estimation

Povzetek

Cost estimation is critical for effective decision making in engineering projects. However, it is often hampered by a lack of sufficient data. For this, data imputation techniques can be used to estimate missing costs based on statistical estimates or analogies with historical data. However, these techniques are often limited because they do not consider the existing knowledge of experts. In this paper, a novel cognitive data imputation technique is proposed for cost estimation that uses explanatory interactive machine learning to integrate and improve human knowledge. Through a case study in maintenance cost estimation the effectiveness of the approach is demonstrated.

Ključne besede

artificial intelligence;maintenance;cost estimation;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UL FS - Fakulteta za strojništvo
UDK: 004.8:658.5
COBISS: 158961155 Povezava se bo odprla v novem oknu
ISSN: 0007-8506
Št. ogledov: 5
Št. prenosov: 0
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Slovenski jezik
Sekundarne ključne besede: umetna inteligenca;vzdrževanje;ocena stroškov;
Vrsta dela (COBISS): Članek v reviji
Strani: str. 385-388
Letnik: ǂVol. ǂ72
Zvezek: ǂiss. ǂ1
Čas izdaje: 2023
DOI: 10.1016/j.cirp.2023.03.036
ID: 19574776
Priporočena dela:
, case study in maintenance cost estimation
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