Predicting structure use with machine learning algorithm: Model validation approach for DAP data

Authors

  • A Biswas Department of Urban and Regional Planning, Jahangirnagar University, Savar, Dhaka – 1342, Bangladesh
  • S Roy Department of Urban and Regional Planning, Jahangirnagar University, Savar, Dhaka – 1342, Bangladesh
  • T A Shawon Department of Urban and Regional Planning, Jahangirnagar University, Savar, Dhaka – 1342, Bangladesh
  • M M Rahman Department of Urban and Regional Planning, Jahangirnagar University, Savar, Dhaka – 1342, Bangladesh

DOI:

https://doi.org/10.3329/jbip.v16i1.77039

Keywords:

Machine learning, structure use prediction, decision tree classifier, DAP, Python

Abstract

Machine learning techniques have been successfully applied in many fields, including urban planning. The focus of this article is to develop a machine learning model to automatically predict the use of structures. Automatic predictions can help mitigate the heavy load on urban planners in the early stages of decision-making and provide a quick preview of the scenario. In this study, building data from the Detail Area Plan of Dhaka were used. The number of floors and basements in a structure, the structure's age, the number of dwelling units and the structure type were the independent variables for this research. Due to the dataset's inclusion of both numeric and string data, the Decision Tree (DT) classifier was used for prediction. Python routines were used for data cleaning, model development, and model evaluation. The Scikit-learn Python package, primarily used for ML implementation, was utilized to develop the model. The model had an accuracy rate of 91% for predicting the use of institutional, education and research, mixed use, health facilities, under construction, and agriculture structures. Due to incomplete data, residential, restricted and special use, community facilities, miscellaneous, commercial, industrial, transportation and communication use of structures could not be reliably predicted. This model can aid in determining the use of a structure based on the characteristics of the structure (floor, basement, structure type, structure age, dwelling unit), based on historical data for that location. The model demonstrates the use of machine learning in urban planning.

JBIP, Vol. 16, 2023, pp. 19-39

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Published

2025-02-12

How to Cite

Biswas, A., Roy, S., Shawon, T. A., & Rahman, M. M. (2025). Predicting structure use with machine learning algorithm: Model validation approach for DAP data. Journal of Bangladesh Institute of Planners, 16(1), 19–39. https://doi.org/10.3329/jbip.v16i1.77039

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Articles