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Data-Driven Housing Damage and Repair Cost Prediction Framework Based on The 2010 Kraljevo Earthquake Data
(16th World Conference on Earthquake Engineering (16WCEE), 2017)
This paper presents an earthquake damage and repair cost prediction framework for individual residential buildings and portfolios of residential buildings in a municipal area in a region where the seismological networks ...
Upravljanje rizicima pri izgradnji kapitalnih infrastrukturnih objekata u cilju poboljšanja njihove održivosti / Risk management during planning and construction of large infrastructure projects for improving their sustainability
(Универзитет у Београду, Грађевински факултет, 2015)
Investicioni projekat u građevinarstvu se definiše kao kompleksan tehničko-tehnološki,organizacioni, pravni, ekonomski i finansijski poduhvat koji se sastoji od skupakoordinisanih i kontrolisanih aktivnosti sa jasno ...
Construction cost estimation of reinforced and prestressed concrete bridges using machine learning
(Građevinar, 2021)
Seven state-of-the-art machine learning techniques for estimation of construction
costs of reinforced-concrete and prestressed concrete bridges are investigated in this
paper, including artificial neural networks (ANN) ...
Primena mašinskog učenja za procenu cena i količina radova pri izgradnji stambenih i stambeno-poslovnih objekata
(Udruženje inženjera građevinarstva, geotehnike, arhitekture i urbanista "Izgradnja", 2021)
Ovaj rad se bavi problemom procena potrebnih količina radova, kao i koštanja izgradnje stambenih i stambeno-poslovnih objekata korišćenjem algoritama mašinskog učenja. Osnovni cilj je analiza mogućnosti primene mašinskog ...
Preliminary quantity estimation in construction using machine learning methods
(STEPGRAD2022 - Proceedings of International conference on Contemporary Theory and Practice in Construction XV, 2022)
This paper analyses the problem of estimating the required quantities of major work items in the construction of residential and residential-commercial buildings using machine learning algorithms. The goal is to form a ...
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 ...
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 ...