How to search?
advanced search

Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 5
items per page: 25 50 75
Sort by:

Pre-design cost modeling of facade systems using the GAM method

Agnieszka Leśniak Monika Górka
Archives of Civil Engineering | 2021 | vol. 67 | No 3 | 123-138 | DOI: 10.24425/ace.2021.138047
Keywords facade systems for public buildings cost estimates Generalized Additive Models (GAM)
Download PDF Download RIS Download Bibtex

Abstract

The cost estimation at the pre-project stage provides an important decision-making indicator for the future of the project. With a preliminary cost estimation, project participants can make financial decisions and cost control. The aim of this paper is to propose a model for estimating the costs of facade systems before the pre-design stage, using the GAM (Generalized Additive Model) method. The commonly used method for the valuation of facade systems is based on individual calculation. Such valuation process is complicated and time consuming. For this reason the search for a new forecasting method is justified. The database developed for modelling purposes includes 61 cases of real costs of system façade execution for public buildings. Each case is described by 16 parameters (namely, input variables). The average absolute percentage error (MAPE) was used to assess the model, which takes the value of 14,26% for the generalized model with a logarithmic binding function and 11.77% for the model with an identity binding function. On the basis of the studies and the results obtained, it can be concluded that the constructed model is useful and can improve the process of forecasting system façade costs at the pre-projection stage.
Go to article

Bibliography


[1] D. A. Aczel, “Statystyka w Zarządzaniu”, Wydawnictwo Naukowe PWN, 2017.
[2] H. Anysz, „Managing Delays in Construction Projects Aiming at Cost Overrun Minimization”, In IOP Conference Series: Materials Science and Engineering, Vol. 603, No. 3, 2004, 2019. https://doi.org/10.1088/1757-899X/603/3/032004
[3] A. Belusic, I. Herceg-Bulic, Z. Bencetic Klaic, “Using a generalized additive model to quantify the influence of local meterology on air quality in Zagreb”, Geofizyka, Vol. 32, No. 5, pp. 47–77, 2015. https://doi.org/10.15233/gfz.2015.32.5
[4] K. Coussement, D. F. Benoit, D. Van den Poel, “Improved marketing decision making in a customer churn prediction context using generalized additive models”, Expert Systems with Applications, Vol. 37, No. 3, pp. 2132–2143, 2009.
[5] M. S. El-Abbasy, t. Zayed, “Generic scheduling optimization model for multiple construction projects”, Journal of computing in civil engineering, Vol. 31, No. 4, 04017003, 2017. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000659
[6] M. Górka, „Use of aluminium and glass facades in urban architecture”, Budownictwo i Architektura, Vol. 18, No. 3, pp. 29–40, 2019. https://doi.org/10.35784/bud-arch.586
[7] T. J. Hastii, R. J. Tibshirani, „Generalized Additive Models”, Chapman & Hall/CRC Monographs on Statistics & Applied Probability, 1990.
[8] M. Juszczyk, “Residential buildings conceptual cost estimates with the use of support vector regression”, In MATEC Web of Conferences, Vol. 196, 04090, 2018.
[9] M. Juszczyk, K. Zima, W. Lelek, „Forecasting of sports fields construction costs aided by ensembles of neural networks”, Journal of Civil Engineering and Management, Vol. 25, No. 7, pp. 715–729, 2019. https://doi.org/10.3846/jcem.2019.10534
[10] P. Kamble, N. Sanadi, “Optimization of Time and Cost of Building Construction using Fast Tracking Method of Scheduling”, Optimization, Vol. 6, No. 07, 2019.
[11] O. Kapliński, “Problematyka inżynierii przedsięwzięć budowlanych na konferencjach krynickich 2017 i 2018”, Przegląd Budowlany, 89, 2018.
[12] T. Kasprowicz, „Inżynieria przedsięwzięć budowlanych. Metody i modele w Inżynierii przedsięwzięć budowlanych”, Pr. zb. pod red. Kapliński Oleg, PAN KILiW, IPPT, 2007.
[13] M. Kozlovska, M. Spisakova, D. Mackova, „Identifying the construction waste types relating to modern methods of construction”, Book Series: International Multidisciplinary Scientific GeoConference SGEM, pp. 129–136, 2016. https://doi.org/10.5593/SGEM2016/B62/S26.018
[14] M. Krzemiński, “Optimization of work schedules executed using the flow shop model, assuming multitasking performed by work crews”, Archives of Civil Engineering, Vol. 63, No. 4, pp. 3–19, 2017. https://doi.org/10.1515/ace-2017-0037
[15] A. Kylili, P.A. Fokaides, “Policy trends for the sustainability assessment of construction materials: A review”, Sustainable Cities and Society, Vol. 35, pp. 280–288, 2017. https://doi.org/10.1016/j.scs.2017.08.013
[16] A. Leśniak, M. Górka, “Analysis of the cost structure of aluminum and glass facades”, In Advances and Trends in Engineering Sciences and Technologies III: Proceedings of the 3rd International Conference on Engineering Sciences and Technologies (ESaT 2018), CRC Press, 445, 2019. https://doi.org/10.1201/9780429021596-70
[17] A. Leśniak, M. Górka, D. Wieczorek, „Identification of factors shaping tender prices for lightweight”, Scientific Review Engineering and Environmental Sciences, Vol. 2, pp. 171–182, 2019. https://doi.org/10.22630/PNIKS.2019.28.2.16
[18] A. Leśniak, F. Janowiec. “Risk Assessment of Additional Works in Railway Construction Investments Using the Bayes Network”, Sustainability, Vol. 11, No. 19, pp. 53–88, 2019. https://doi.org/10.3390/su11195388
[19] A. Leśniak, M. Juszczyk, “Prediction of site overhead costs with the use of artificial neural network based model”, Archives of Civil and Mechanical Engineering, Vol. 18, No. 3, pp. 973–982, 2018. https://doi.org/10.1016/j.acme.2018.01.014
[20] A. Leśniak, M. Juszczyk, G. Piskorz, „Modelling Delays in Bridge Construction Projects Based on the Logit and Probit Regression”, Archives of Civil Engineering, Vol. 65, No. 2, pp. 107–120, 2019. http://doi.org/10.2478/ace-2019-0022
[21] A. Leśniak, K. Zima, „Cost calculation of construction projects including sustainability factors using the Case Based Reasoning (CBR) method”, Sustainability, Vol. 10, No. 5, 1608, 2018. https://doi.org/10.3390/su10051608
[22] P. Mccullagh, J.A. Nelder, “Generalized Linear models”, Chapman and Hall, 1989.
[23] M. Mrówczyńska, M. Sztubecka, M. Skiba, A. Bazan-Krzywoszańska, P. Bejga, „The Use of Artificial Intelligence as a Tool Supporting Sustainable Development Local Policy”, Sustainbility, Vol. 11, No. 15, 4199, 2019. https://doi.org/10.3390/su11154199
[24] T. Nivea, T. Anu V, “Regression modelling for prediction of construction cost and duration”, In: Applied Mechanics and Materials. Trans Tech Publications, pp. 195–199, 2017. https://doi.org/10.4028/www.scientific.net/AMM.857.195
[25] B. Nowogońska, J. Korentz, “Value of Technical Wear and Costs of Restoring Performance Characteristics to Residential Buildings”, Buildings, Vol. 10, No. 1, pp. 2075–5309, 2020. https://doi.org/10.3390/buildings10010009
[26] A. Oke, C. Aigbavboa, E. Dlamini, “Factors Affecting Quality of Construction Projects in Swazilland”, In Conference: Conference: 9th International Conference on Construction in the 21st Century, At Dubai, UAE, 2017.
[27] A. Panwar, K.N. Jha, “A many-objective optimization model for construction scheduling”, Construction management and economics, Vo. 37, No. 12, pp. 727–739, 2019. https://doi.org/10.1080/01446193.2019.1590615
[28] Z. Rachid, B. Toufik, B. Mohammed, “Causes of schedule delays in construction projects in Algeria”, International Journal of Construction Management, Vol. 19, No. 5, pp. 371–381, 2019. https://doi.org/10.1080/15623599.2018.1435234
[29] M. Rogalska, “Prognozowanie rzeczywistego zużycia mieszanki betonowej do wykonania ścian szczelinowych metodą uogólnionych modeli addytywnych GAM”, Materiały Budowalne, Vol. 6, pp. 88–89, 2016.
[30] M. Rogalska, „Wieloczynnikowe modele w prognozowaniu czasu procesów budowlanych”, Politechnika Lubelska, 2016. https://doi.org/10.15199/33.2016.06.38
[31] M. Rogalska, P. Wolski, „Prognozowanie ceny 1m2 mieszkania na rynku pierwotnym w warszawie metodą uogólnionych modeli addytywnych”, Logistyka, Vol. 6, pp. 9101–9110, 2014.
[32] M. Saeedi, “Study the Effects of Constructions New Techniques and Technologies on Time, Cost and Quality of Construction Projects from the Perspective of Construction Management”, Journal of Civil Engineering and Materials Application, Vol. 1, No. 2, pp. 61–76, 2017.
[33] S.S. Shaikh, M.M. Darade, “Key performance indicator for measuring and improving quality of construction projects”, International Research Journal of Engineering and Technology (IRJET), Vol. 4, No. 5, pp. 2133–2139, 2017.
[34] D. Skorupka, A. Duchaczek, M. Kowacka, P. Zagrodnik, „Quantification of geodetic risk factors occurring at the construction project preparation stage”, Archives of Civil Engineering, Vol. 64, No. 3, pp. 195–200, 2018. https://doi.org/10.2478/ace-2018-0039
[35] M. Sztubecka, M. Skiba, M. Mrówczyńska, A. Bazan-Krzywoszańska, „An Innovative Decision Support System to Improve the Energy Efficiency of Buildings in Urban Areas”, Remote Sensing, Vol. 12, No. 2, 259, 2020. https://doi.org/10.3390/rs12020259
[36] Y. Wang, B. Yu, J. Wei, F. Li, „Direct numerical simulation on drag-reducing flow by polymer additives using a spring-dumbbell model”, Progress in Computational Fliud Dynamics, an International Journal, Vol. 9, 2009. https://doi.org/10.1504/PCFD.2009.024822
[37] D. Wieczorek, E. Plebankiewicz, K. Zima, „Model estimation of the whole life cost of a building with respect to risk factors”, Technological and Economic Development of Economy, Vol. 25 No. 1, pp. 20–38, 2019. https://doi.org/10.3846/tede.2019.7455
Go to article

Authors and Affiliations

Agnieszka Leśniak
1
ORCID: ORCID
Monika Górka
1
ORCID: ORCID
  1. Cracow University of Technology, Faculty of Civil Engineering, Institute, 24 Warszawska street, 31-155 Cracow, Poland

Factors Affecting Workforce at Construction Site

Edyta Plebankiewicz Agnieszka Leśniak Patrycja Karcińska
Archives of Civil Engineering | Vol. 66 | No 2 | 77-88 | DOI: 10.24425/ace.2020.131797
Keywords construction employment planning assessment of expert opinion
Download PDF Download RIS Download Bibtex

Abstract

The article presents the results of research carried out in construction companies among employees involved in the organisation and management of construction projects. The research concerned factors and their impact on decisions regarding the planning of quantitative employment workforce at a construction site. Based on individual assessments of individual factors, average assessments were calculated and hierarchies of the factors examined were made. In the second part of the article, the dispersion coefficient of relative classification was used to assess the reliability of the opinions collected. The content presented is a continuation of the work of the authors on the subject of employment planning at the construction site.

Go to article

Authors and Affiliations

Edyta Plebankiewicz
ORCID: ORCID
Agnieszka Leśniak
ORCID: ORCID
Patrycja Karcińska

Costs of Facade Systems Execution

Agnieszka Leśniak Damian Wieczorek Monika Górka
Archives of Civil Engineering | Vol. 66 | No 1 | 81-95 | DOI: 10.24425/ace.2020.131776
Keywords facade systems cost estimation statistical models multiple regression stepwise regression
Download PDF Download RIS Download Bibtex

Abstract

Cost estimation in the pre-design phase both for the contractor as well as the investor is an important aspect from the point of view of budget planning for a construction project. Constantly growing commercial market, especially the one of public utility constructions, makes the contractor, at the stage of development the design concept, initially estimate the cost of the facade, e.g. office buildings, commercial buildings, etc., which are most often implemented in the form of aluminum-glass facades or ventilated elevations. The valuation of facade systems is of an individual calculation nature, which makes the process complicated, time-consuming, and requiring a high cost estimation work. The authors suggest using a model for estimating the cost of facade systems with the use of statistical methods based on multiple and stepwise regression. The data base used to form statistical models is the result of quantitative-qualitative research of the design and cost documentation of completed public facilities. Basing on the obtained information, the factors that shape the costs of construction façade systems were identified; which then constitute the input variables to the suggested cost estimation models.

Go to article

Authors and Affiliations

Agnieszka Leśniak
ORCID: ORCID
Damian Wieczorek
ORCID: ORCID
Monika Górka
ORCID: ORCID

Models for estimating costs of public buildings maintaining – review and assessment

Edyta Plebankiewicz Agnieszka Leśniak Eva Vitkova Vit Hromadka
Archives of Civil Engineering | 2022 | vol. 68 | No 1 | 335-351 | DOI: 10.24425/ace.2022.140171
Keywords building maintenance life cycle cost cost calculation
Download PDF Download RIS Download Bibtex

Abstract

Planning maintenance costs is not an easy task. The amount of costs depends on many factors, such as value, age, condition of the property, availability of necessary resources and adopted maintenance strategy. The paper presents a selection of models which allow to estimate the costs of building maintenance, which are then applied to an exemplary office building. The two of the models allow a quick estimation of the budget for the maintenance of the building, following only indicative values. Two other methods take into account the change in the value of money over time and allow to estimate, assuming the adopted strategy and assumed costs, the value of the current amount allocated to the maintenance of the building. The final model is based on the assumptions provided for in Polish legislation. Due to significant simplifications in the models, the obtained results are characterized by a considerable discrepancy. However, they may form the basis for the initial budget planning related to the maintenance of the building. The choice of the method is left to the decision makers, but it is important what input data the decision maker has and the purpose for which he performs the cost calculation.
Go to article

Authors and Affiliations

Edyta Plebankiewicz
1
ORCID: ORCID
Agnieszka Leśniak
1
ORCID: ORCID
Eva Vitkova
2
ORCID: ORCID
Vit Hromadka
2
ORCID: ORCID
  1. Cracow University of Technology, Faculty of Civil Engineering, Warszawska 24, 31-155 Kraków, Poland
  2. Brno University of Technology, Faculty of Civil Engineering, Veverí 331/95, 602 00 Brno, Czech Republik

Photogrammetry-based approach for collecting and processing information about an existing building

Robertas Kontrimovicius Michał Juszczyk Agnieszka Leśniak Leonas Ustinovichius Czesław Miedziałowski
Bulletin of the Polish Academy of Sciences Technical Sciences | 2023 | 71 | 1 | e144453 | DOI: 10.24425/bpasts.2023.144453
Keywords photogrammetry building information modelling building model development quantity take-off construction works information processing
Download PDF Download RIS Download Bibtex

Abstract

Due to the organization of construction works, one of the most difficult situations is when a building is planned in a heritage or a densely built-up location. Fixing an existing situation manually takes a lot of time and effort and is usually not accurate. For example, it is not always possible to measure the exact spacing between buildings at different levels and to consider all outside elements of an existing building. Improper fixation of the existing situation causes mistakes and collisions in design and the use of inappropriate construction solutions. The development and progress in technologies such as BIM, laser scanning, and photogrammetry broaden the options for supporting the management of construction projects. It is important to have an effective fast collection and processing of useful information for management processes. The purpose of this paper is to analyze and present some aspects of photogrammetry to collect and process information about existing buildings. The methodology of the study is based on the comparison of two alternative approaches, namely photogrammetry and BIM modelling. Case studies present an analysis of the quantity take-offs for selected elements and parts of the buildings based on the two approaches. In this article, the specific use of photogrammetry shows that the error between the detailed BIM model and the photogrammetry model is only 1.02% and the accuracy is 98.98%. Moreover, physical capabilities do not always allow us to measure every desired element in reality. This is followed by a discussion on the usability of photogrammetry.
Go to article

Authors and Affiliations

Robertas Kontrimovicius
1
ORCID: ORCID
Michał Juszczyk
2
ORCID: ORCID
Agnieszka Leśniak
2
ORCID: ORCID
Leonas Ustinovichius
1
ORCID: ORCID
Czesław Miedziałowski
3
ORCID: ORCID
  1. Faculty of Civil Engineering, Vilnius Gediminas Technical University, Lithuania
  2. Faculty of Civil Engineering, Cracow University of Technology, Poland
  3. Faculty of Civil Engineering and Environmental Sciences, Bialystok University of Technology, Poland

This page uses 'cookies'. Learn more