IDEAS home Printed from https://ideas.repec.org/a/hin/complx/7952434.html
   My bibliography  Save this article

ANN Based Approach for Estimation of Construction Costs of Sports Fields

Author

Listed:
  • Michał Juszczyk
  • Agnieszka Leśniak
  • Krzysztof Zima

Abstract

Cost estimates are essential for the success of construction projects. Neural networks, as the tools of artificial intelligence, offer a significant potential in this field. Applying neural networks, however, requires respective studies due to the specifics of different kinds of facilities. This paper presents the proposal of an approach to the estimation of construction costs of sports fields which is based on neural networks. The general applicability of artificial neural networks in the formulated problem with cost estimation is investigated. An applicability of multilayer perceptron networks is confirmed by the results of the initial training of a set of various artificial neural networks. Moreover, one network was tailored for mapping a relationship between the total cost of construction works and the selected cost predictors which are characteristic of sports fields. Its prediction quality and accuracy were assessed positively. The research results legitimatize the proposed approach.

Suggested Citation

  • Michał Juszczyk & Agnieszka Leśniak & Krzysztof Zima, 2018. "ANN Based Approach for Estimation of Construction Costs of Sports Fields," Complexity, Hindawi, vol. 2018, pages 1-11, March.
    • Handle: RePEc:hin:complx:7952434
    DOI: 10.1155/2018/7952434
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2018/7952434.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2018/7952434.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2018/7952434?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Trefor Williams, 2002. "Predicting completed project cost using bidding data," Construction Management and Economics, Taylor & Francis Journals, vol. 20(3), pages 225-235.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maria Mrówczyńska & Marta Skiba & Anna Bazan-Krzywoszańska & Dorota Bazuń & Mariusz Kwiatkowski, 2018. "Social and Infrastructural Conditioning of Lowering Energy Costs and Improving the Energy Efficiency of Buildings in the Context of the Local Energy Policy," Energies, MDPI, vol. 11(9), pages 1-16, September.
    2. Maria Mrówczyńska & Małgorzata Sztubecka & Marta Skiba & Anna Bazan-Krzywoszańska & Przemysław Bejga, 2019. "The Use of Artificial Intelligence as a Tool Supporting Sustainable Development Local Policy," Sustainability, MDPI, vol. 11(15), pages 1-17, August.
    3. Zhengxun Jin & Jonghyeob Kim & Chang-taek Hyun & Sangwon Han, 2019. "Development of a Model for Predicting Probabilistic Life-Cycle Cost for the Early Stage of Public-Office Construction," Sustainability, MDPI, vol. 11(14), pages 1-18, July.
    4. Edyta Plebankiewicz & Damian Wieczorek, 2020. "Prediction of Cost Overrun Risk in Construction Projects," Sustainability, MDPI, vol. 12(22), pages 1-15, November.
    5. Agnieszka Leśniak & Filip Janowiec, 2019. "Risk Assessment of Additional Works in Railway Construction Investments Using the Bayes Network," Sustainability, MDPI, vol. 11(19), pages 1-15, September.
    6. Edyta Plebankiewicz & Jakub Gracki, 2021. "Analysis of the Impact of Input Data on the Planned Costs of Building Maintenance," Sustainability, MDPI, vol. 13(21), pages 1-16, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kim Young Joo & Skibniewski Miroslaw J., 2020. "Unsuccessful bids: Coefficient of variation of bids as indicator of project risk," Organization, Technology and Management in Construction, Sciendo, vol. 12(1), pages 2193-2199, January.
    2. Wei Tong Chen & Ying-Hua Huang, 2006. "Approximately predicting the cost and duration of school reconstruction projects in Taiwan," Construction Management and Economics, Taylor & Francis Journals, vol. 24(12), pages 1231-1239.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:complx:7952434. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.