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Allocation and Selection of equipment for concrete works using Fuzzy Linear Programming
(Belgrade, Serbia: Society for Materials and Structures Testing of SerbiaBelgrade, Serbia: University of Belgrade Faculty of Civil EngineeringBelgrade, Serbia : Association of Structural Engineers of Serbia, 2021)
The aim of this research is focused on the problem of allocation and selection of the construction equipment when construction firms bid for construction projects. The main objective of the selection of construction equipment ...
Uticaj konstruktivnog sistema na troškove i trajanje građenja stambenih objekata / The influence of superstructure type on cost and duration of residential projects
(Gradjevinar, 2019)
The aim of the research is to investigate the impact of the superstructure system type on cost and duration of residential projects, as well as the identification and quantification of the key parameters that affect them ...
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 ...
Application of Artificial Intelligence for the Estimation of Concrete and Reinforcement Consumption in the Construction of Integral Bridges
(Hindawi, 2020)
Estimation of basic material consumption in civil engineering is very important in the initial phases of project implementation. Its
importance is reflected in the impact of material quantities on forming the prices of ...
One modification of fuzzy TOPSIS method
(Emerald Group Publishing Limited, 2013)
Purpose
The purpose of this paper is to present one modification of the fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and to develop a corresponding computer program which could be used for ...
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 ...
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 ...
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 ...