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Forecasting of safe-green buildings using decision tree algorithm: data mining approach

Author

Listed:
  • Alireza Motaghifard

    (Islamic Azad University Qazvin Branch)

  • Manouchehr Omidvari

    (Islamic Azad University Qazvin Branch)

  • Abolfazl Kazemi

    (Islamic Azad University Qazvin Branch)

Abstract

Nowadays, buildings and the environment are considered as national assets. The forecasting and identification of the factors affecting the construction of safe-green buildings are of great importance. The present study seeks to identify effective models and patterns using the data mining technique and decision tree algorithms. This research was conducted on 622 buildings, such that the sampling process was performed by census method. Clementine software was used to analyze the data. In the present study, the CHAID, QUEST, CART, and C5 algorithms were implemented, predicted, and compared on the dataset. Variables were used in four fields of health, safety, environment, and energy management (HSEE), as well as four scopes of structure, architecture, mechanical facilities, and electrical installations as predictive variables of the decision tree. The situation of construction competency was addressed as a dependent binary variable from the perspective of the safe-green building. The results of the decision tree analysis showed that the type of glass, fire alarm system, and emergency rescue system in the field of safety and energy management, health and type of structure (consumables) in the field of environment in the classification of buildings based on safe-green model were of the highest importance. By developing a model based on data mining techniques and considering the simple interpretation of the decision tree and the comprehensibility of its extracted rules, the results of this research can help building experts at different levels of decision-making and in all stages of construction, operation, building rating, and the definition of determining premiums.

Suggested Citation

  • Alireza Motaghifard & Manouchehr Omidvari & Abolfazl Kazemi, 2023. "Forecasting of safe-green buildings using decision tree algorithm: data mining approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 10323-10350, September.
    • Handle: RePEc:spr:endesu:v:25:y:2023:i:9:d:10.1007_s10668-022-02491-4
    DOI: 10.1007/s10668-022-02491-4
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    References listed on IDEAS

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