This article 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 damage probability distribution that, combined with an expert-defined repair cost matrix, enables the calculation of the expected repair costs for each building and, in aggregate, of direct losses in the earthquake-affected area. The proposed building representation does not include explicit information about the earthquake and the soil type. Instead, such information is implicitly contained in the spatial distribution of damage. To capture this distribution, a sampling algorithm, based on K-means clustering, is used to select a minimal number of buildings that represent the area of interest in terms of its seismic risk, independently of future earthquakes. To observe damage states in the representative set after an earthquake, the proposed framework utilizes a local network of trained damage assessors. The model is updated after each damage observation cycle, thus increasing the accuracy of the current loss assessment. The proposed framework is exemplified using the 2010 Kraljevo, Serbia earthquake dataset.
Cost estimates in the early stages of project development are essential for making the right decisions, but they are a huge challenge and risk for owners and potential contractors due to limited ...information about the characteristics of a future highway project. Whereas previous studies were mainly focused on achieving the highest possible estimation accuracy, this paper aims to propose cost-estimation models that can provide satisfactory accuracy with the least possible effort and to compare the perspectives of owners and contractors as the key stakeholders on projects. To determine cost drivers (CDs) that have a high influence on highway-construction costs and require low effort for their establishment, a questionnaire survey was conducted. Based on the key stakeholders’ perceptions and collected data set, cost-estimation models were developed using multiple-regression analysis, artificial neural networks, and XGBoost. The results show that reasonable cost-estimation accuracy can be achieved with relatively low effort for three CDs for the owners’ perspective and five CDs for the contractors’ perspective. Additional inclusion of input CDs in models does not necessarily imply an increase in accuracy. Also, the questionnaire results show that owners are more concerned about environmental issues, whereas contractors are more concerned about the possible changes in resource prices (especially after recent high increases caused by COVID-19 and the Russia–Ukraine war). These findings can help owners and potential contractors in intelligent decision-making in the early stages of future highway-construction projects.
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 research is unbiased CoD detection at a single project level, with the ultimate goal to discover the root causes of delay. The existing approach is based on expert knowledge which is used to create CoD lists for projects in general or groups of similar projects. When applied to a single project, it is burdened with bias, as shown on a case project returning low Spearman Rank correlation values. This research introduces a Delay Root causes Extraction and Analysis Model—DREAM. The proposed model combines expert knowledge, machine learning techniques, and Minutes of Meetings (MoM) as an unutilized extensive source of information. In the first phase, DREAM outputs a CoD list based on occurring frequency in MoM with satisfactory recall values, significantly reducing expert-induced subjectivism. In the second phase, enabled by MoM dates, DREAM adds another dimension to delay analysis—temporal CoD distribution. By analyzing corresponding informative charts, experts can understand the nature of delays and discover the root CoD, allowing intelligent decision making on future projects.
The relationship between the quality of finishing works, costs, market value, and profit, is presented and explained for residential buildings. The results show that the higher quality of finishing ...works increases profit for investors. As the maximum market price is limited, there is a limit when the investment in finishing work is no longer cost-effective as, after increase in costs, the market value decreases and the profit reduces. The research methodology presented in the paper can be applied to any residential real estate market.
Work cycle based scheduling Dejan Marinković; Zoran Stojadinović; Nenad Ivanišević
Građevinar (Zagreb),
12/2013, Letnik:
65, Številka:
11
Journal Article
Odprti dostop
The paper proposes a new approach to short-term scheduling based on spatial and technological cycles, continuous crew flows and daily scheduling, named WCBS (Work Cycle Based Scheduling). Application ...of WCBS is shown on a case study of constructing seven multi-storey structures. It was concluded that WCBS helps overcome restrictions of existing approaches to micro scheduling (daily tasks and crew coordination), enhances the scheduling process and increases productivity of works.
The aim of the research is to investigate the ways in which various structural systems and time influence the cost of construction of RC structures of residential buildings, and to identify and ...quantify key parameters that are of highest significance in this respect. The data taken from the database of completed projects are analysed using the leave-one-out-cross-validation and regression analysis. Limit numerical values confirmed by the redesign of two structures from the database are identified as key parameters. These values define in quantitative terms the rationality of the design solution and the rationality of construction work scheduling. They can also be used in practice in order to optimise the cost and time of construction work on residential buildings.
Cilj istraživanja je ispitivanje utjecaja vrste konstrukcijskog sustava i trajanje na troškove građenja AB konstrukcije stambenih objekata, kao i identifikacija i kvantifikacija ključnih parametara ...koji na to najviše utječu. Podaci iz baze dovršenih projekata ocijenjeni su primjenom jednostrukog unakrsnog ocjenjivanja i regresijske analize. Za ključne parametre identificirane su granične numeričke vrijednosti koje su potvrđene preprojektiranjem dvaju objekata iz baze. Te vrijednosti na kvantificiran način definiraju racionalnost projektantskog rješenja kao i racionalnost planiranja organizacije građenja. Mogu se primijeniti i u praksi s ciljem racionaliziranja troškova i trajanja građenja stambenih objekata.
This article presents a taxonomy and represents a repository of open problems in computing for numerically and logically intensive problems in a number of disciplines that have to synergize for the ...best performance of simulation-based feasibility studies on nature-oriented engineering in general and civil engineering in particular. Topics include but are not limited to: Nature-based construction, genomics supporting nature-based construction, earthquake engineering, and other types of geophysical disaster prevention activities, as well as the studies of processes and materials of interest for the above. In all these fields, problems are discussed that generate huge amounts of Big Data and are characterized with mathematically highly complex Iterative Algorithms. In the domain of applications, it has been stressed that problems could be made less computationally demanding if the number of computing iterations is made smaller (with the help of Artificial Intelligence or Conditional Algorithms), or if each computing iteration is made shorter in time (with the help of Data Filtration and Data Quantization). In the domain of computing, it has been stressed that computing could be made more powerful if the implementation technology is changed (Si, GaAs, etc.…), or if the computing paradigm is changed (Control Flow, Data Flow, etc.…).
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 of other related fields. The course derived from this strategy includes four parts: (a) Computing with a selected set of modern paradigms—the stress is on Control Flow and Data Flow computing paradigms, but paradigms conditionally referred to as Energy Flow and Diffusion Flow are also covered; (b) Project management that is holistic—the stress is on the wide plethora of issues spanning from the preparation of project proposals, all the way to incorporation activities to follow after the completion of a successful project; (c) Examples from past research and development experiences—the stress is on experiences of leading experts from academia and industry; (d) Student projects that stimulate creativity—the stress is on methods that educators could use to induce and accelerate the creativity of students in general. Finally, the article ends with selected pearls of wisdom that could be treated as suggestions for further elaboration.
PDF
