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Now showing items 41-45 of 45
Rapid earthquake loss assessment based on machine learning and representative sampling
(Earthquake Spectra, 2021)
This paper proposes a new framework for rapid earthquake loss assessment based on a machine learning damage classification model and a representative sampling algorithm. A Random Forest classification model predicts a ...
Detection and In-Depth Analysis of Causes of Delay in Construction Projects: Synergy between Machine Learning and Expert Knowledge
(Sustainability, 2022)
Due to numerous reasons, construction projects often fail to achieve the planned duration. Detecting causes of delays (CoD) is the first step in eliminating or mitigating potential delays in future projects. The goal of ...
Application of unstructured text based features in prediction of real estate prices: A comparative study
(2nd Serbian International Conference on Applied Artificial Intelligence (SICAAI) Kragujevac, Serbia, May 19-20, 2023, 2023)
This study demonstrates the potential of application of unstructured textual data for predicting
real estate prices and compares different protocols for extracting features from textual data.
Performance of the different ...
Primena BIM-a u upravljanju projektima - kako boljim projektovanjem smanjiti probleme u izvođenju
(Konferencija - 16. kongres DGKS 2022, 28 - 30. 9, Aranđelovac, 2022)
Uspešno upravljanje projektima podrazumeva maksimalno ostvarenje ciljeva projekta uz minimalne probleme u realizaciji. Preduslov za prvo je kreativni a za drugo tehnički kvalitet projektovanja. U radu je predstavljen model ...
Compensating the lack of big data in construction industry with expert knowledge: a case study
(1st Serbian International Conference on Applied Artificial Intelligence (SICAAI) Kragujevac, Serbia, May 19-20, 2022, 2022)
Due to various reasons, there is a lack of big data in the construction industry, one of the main obstacles to a broader implementation of AI. Another obstacle is adhering to analytical methods in fields more suitable for ...