Vol.10, No.3, August 2021.                                                                                                                                                                               ISSN: 2217-8309

                                                                                                                                                                                                                         eISSN: 2217-8333

 

TEM Journal

 

TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS

Association for Information Communication Technology Education and Science


Application Machine Learning in Construction Management

 

Phong Thanh Nguyen

 

© 2021 Phong Thanh Nguyen, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)

 

Citation Information: TEM Journal. Volume 10, Issue 3, Pages 1385-1389, ISSN 2217-8309, DOI: 10.18421/TEM103-48, August 2021.

 

Received: 13 January 2021.

Revised:   03 August 2021.
Accepted: 10 August 2021.
Published: 27 August 2021.

 

Abstract:

 

Machine Learning is a subset and technology developed in the field of Artificial Intelligence (AI). One of the most widely used machine learning algorithms is the K-Nearest Neighbors (KNN) approach because it is a supervised learning algorithm. This paper applied the K-Nearest Neighbors (KNN) algorithm to predict the construction price index based on Vietnam's socio-economic variables. The data to build the prediction model was from the period 2016 to 2019 based on seven socio-economic variables that impact the construction price index (i.e., industrial production, construction investment capital, Vietnam’s stock price index, consumer price index, foreign exchange rate, total exports, and imports). The research results showed that the construction price index prediction model based on the K-Nearest Neighbors (KNN) regression method has fewer errors than the traditional method.

 

Keywords : Artificial Intelligence, construction engineering, K-Nearest Neighbors (KNN), machine learning, construction price index, construction management.

 

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