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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 ...
A digital solution for unlocking the urban mining potential of the residential building stock through the integration of BIM and GIS
(Conference on interdisciplinary and transdisciplinary research for sustainable development, 2022)
The construction industry consumes up to half of the excavated primary resources and
generates one-third of total waste annually, impacting the environment and society. To
reduce this impact, maintaining the primary ...
Geometry as a common ground for BMS and BIM
(IABSE Symposium, Prague 2022: Challenges for Existing and Oncoming Structures, 2022)
Bridge Management Systems (BMSs) are sophisticated software tools, widely used for managing bridges. Comprising a centralized database of all relevant information for the entire bridge stock and analytics to forecast ...
2010 Kraljevo Earthquake Recovery Process Metrics Derived from Recorded Reconstruction Data
(16th European Conference on Earthquake Engineering, 2018)
Earthquake resilience starts with a sudden drop of performance when an earthquake strikes followed by a relatively long recovery phase. The dynamics and volume of investment directly affect the rate and level of recovery. ...
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 ...
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 ...
Tehnologija građevinskih radova
(Građevinski fakultet u Beogradu, 2015)
Cost-oriented analysis of fibre reinforced concrete column-supported flat slabs construction
(Journal of Building Engineering, 2022)
Fibre reinforced concrete (FRC) is increasingly being used in elements with high structural responsibility, the constructed FRC column-supported flat slabs (CSFSs, hereinafter) with partial or even total substitution of ...
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 ...