Mathematical models for the prediction of construction duration of building projects : verification and development
Issued Date
2024
Copyright Date
2018
Language
eng
File Type
application/pdf
No. of Pages/File Size
xvi, 184 leaves : ill., map
Access Rights
open access
Rights
ผลงานนี้เป็นลิขสิทธิ์ของมหาวิทยาลัยมหิดล ขอสงวนไว้สำหรับเพื่อการศึกษาเท่านั้น ต้องอ้างอิงแหล่งที่มา ห้ามดัดแปลงเนื้อหา และห้ามนำไปใช้เพื่อการค้า
Rights Holder(s)
Mahidol University
Bibliographic Citation
Thesis (M.Eng. (Civil Engineering))--Mahidol University, 2018
Suggested Citation
Thiri, Kyaw, 1990- Mathematical models for the prediction of construction duration of building projects : verification and development. Thesis (M.Eng. (Civil Engineering))--Mahidol University, 2018. Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/91763
Title
Mathematical models for the prediction of construction duration of building projects : verification and development
Author(s)
Abstract
This research verified Bromilow's Time-Cost and Love et al's Time-Floor models and developed new regression-based models for predicting the actual construction duration for the initial contract stage of building projects in Taunggyi, South Shan State, Myanmar. The data are 26 completed building projects between 2011 - 2017 collected from Taunggyi construction contractors using the survey form. There are three types of models i.e., for overall, for housing and for hotel. The data were divided into two parts. The first part is 80% for modeling which consists of 20, 13 and 6 samples for overall, housing and hotel, respectively. The second part is 20% for validating the resulting models which consist 6, 4 and 1 samples for overall, housing and hotel, respectively. The analysis results showed that among the verified models, BTC model could predict construction duration very well for hotel building with the highest R2 value of 0.851 and has 23.94% mean absolute percentage error (MAPE) based on one validating sample. For the developed models, two multiple linear regression models could predict duration very well for hotel buildings i.e., MLR 7 and MLR 8 with the highest R2 values of 0.995 and 0.995, respectively and have MAPE values of 7.07% and 15.43%, respectively based on one validating sample. All other developed models have rather high predictability with R2 value of around 0.6. Two common variables namely, gross floor area and structural frame type are significant in three model types. In conclusion, all the verified models and proposed models could be applicable as a reference tool for contractors and owners to make a decision in the early stage of building projects and improve constructability of building projects in Taunggyi.
Description
Civil Engineering (Mahidol University 2018)
Degree Name
Master of Engineering
Degree Level
Master's degree
Degree Department
Faculty of Engineering
Degree Discipline
Civil Engineering
Degree Grantor(s)
Mahidol University