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Fire-resistance prognostic model for reinforced concrete columns
(Croatian Association of Civil Engineers, 2012)
The prediction model used for defining fire resistance of reinforced concrete columns exposed to standard fire from all four sides is presented in the paper. The proposed model relies on the concept of artificial neural ...
Early Highway Construction Cost Estimation: Selection of Key Cost Drivers
(MDPI, 2023)
Cost estimates in the early stages of project development are essential for making the right deci-sions, but they are a huge challenge and risk for owners and potential contractors due to limited information about the ...
Urban mining potential in Serbia: Case study of residential building material stock
(Building Materials and Structures, 2022)
As governments worldwide attempt to develop sustainable waste management strategies, massive amounts of waste have been accumulating. However, developing an effective waste management strategy requires a thorough understanding ...
Primena informacionih tehnologija u građevinarstvu / Information technology application in construction industry
(Savez građevinskih inženjera i tehničara Srbije, 2004)
U ovom radu se razmatra primena informacionih tehnologija u građevinskim preduzećima. Primena novih tehnologija otvara nove mogućnosti ali istovremeno pred građevinske firme postavlja i dodatne zahteve. U radu su istaknute ...
Application of artificial neural networks for hydrological modelling in karst
(Union of Croatian Civil Engineers and Technicians, 2018)
The possibility of short-term water flow forecasting in a karst region is presented in this paper. Four state-of-the-art machine learning algorithms are used for the one day ahead forecasting: multi-layer perceptron neural ...
Teaching computing for complex problems in civil engineering and geosciences using big data and machine learning: synergizing four different computing paradigms and four different management domains
(Springer, 2023)
This article describes a teaching strategy that synergizes computing and management, aimed at the running of complex projects in industry and academia, in the areas of civil engineering, physics, geosciences, and a number ...
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 ...
COVID-19 Struggle and Post-COVID-19 Recovery: Exploring the Governance, Success, and Digital Transition in Construction Projects in Serbia
(Sustainability, 2023)
Construction, one of the largest global economic sectors, has been severely challenged by the economic uncertainties brought on by COVID-19. Since 2020, pandemic-related disruptions and remedial measures have made its ...
Broadening the urban sustainable energy diapason through energy recovery from waste: A feasibility study for the capital of Serbia
(Elsevier Ltd, 2017)
Metropolitan areas are large consumers of energy and there is a growing need to broaden the urban sustainable energy diapason and increase the share of renewable and sustainable energy in overall energy consumption. This ...
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 ...