A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Application of machine learning techniques in estimating the construction cost of residential buildings in the Middle East region
The recent global economic crisis resulted in a crash in the real estate market. This has underscored the significance of accurately predicting construction costs for real estate units in the near-term economy. Over the past few decades, there has been limited research conducted on forecasting the construction costs of housing units. Effective cost forecasting, particularly during the early stages, can play a crucial role in minimizing expenses and ensuring the viability of a project. In recent years, the utilization of machine learning techniques has witnessed a significant surge. These techniques offer generalized solutions and demonstrate favorable performance in terms of effort, time, and cost. Therefore, the objective of this paper is to compare the capabilities of different machine learning methods in estimating real estate construction costs. As part of the study, multiple economic variables and indices will be used as inputs for the machine learning models. The paper will also assess and discuss the performance of each technique by comparing it against actual measurements. Ultimately, the aim is to identify the most suitable approach for such cost estimation tasks.
Application of machine learning techniques in estimating the construction cost of residential buildings in the Middle East region
The recent global economic crisis resulted in a crash in the real estate market. This has underscored the significance of accurately predicting construction costs for real estate units in the near-term economy. Over the past few decades, there has been limited research conducted on forecasting the construction costs of housing units. Effective cost forecasting, particularly during the early stages, can play a crucial role in minimizing expenses and ensuring the viability of a project. In recent years, the utilization of machine learning techniques has witnessed a significant surge. These techniques offer generalized solutions and demonstrate favorable performance in terms of effort, time, and cost. Therefore, the objective of this paper is to compare the capabilities of different machine learning methods in estimating real estate construction costs. As part of the study, multiple economic variables and indices will be used as inputs for the machine learning models. The paper will also assess and discuss the performance of each technique by comparing it against actual measurements. Ultimately, the aim is to identify the most suitable approach for such cost estimation tasks.
Application of machine learning techniques in estimating the construction cost of residential buildings in the Middle East region
Alzubi, Yazan (author) / Aljaafreh, Areen (author) / Khatatbeh, Ahmed (author)
International Journal of Construction Management ; 24 ; 946-958
2024-07-03
13 pages
Article (Journal)
Electronic Resource
English
Machine learning application to disaster damage repair cost modelling of residential buildings
| Taylor & Francis Verlag | 2025
Primary Exploration on the Human Elements of Middle East Railway Residential Buildings
| Trans Tech Publications | 2012
Primary Exploration on the Human Elements of Middle East Railway Residential Buildings
| British Library Conference Proceedings | 2012
Control Management of Construction Cost of Prefabricated Residential Buildings
| DOAJ | 2018
Estimating for residential construction
| TIBKAT | 1978