Dopazo, D.A.; Mahdjoubi, L.; Gething, B. An Automated Method for Extracting and Analyzing Railway Infrastructure Cost Data. Buildings2023, 13, 2405.
Dopazo, D.A.; Mahdjoubi, L.; Gething, B. An Automated Method for Extracting and Analyzing Railway Infrastructure Cost Data. Buildings 2023, 13, 2405.
Dopazo, D.A.; Mahdjoubi, L.; Gething, B. An Automated Method for Extracting and Analyzing Railway Infrastructure Cost Data. Buildings2023, 13, 2405.
Dopazo, D.A.; Mahdjoubi, L.; Gething, B. An Automated Method for Extracting and Analyzing Railway Infrastructure Cost Data. Buildings 2023, 13, 2405.
Abstract
The capability of extracting information and analyze it into a common format is essential for performing predictions, comparing projects through cost benchmarking, and for having a deeper understanding of the project costs. However, the lack of standardization and the manual inclusion of the data makes this process very time-consuming, unreliable, and inefficient. To tackle this problem, a novel approach with a big impact is presented combining the benefits of data mining, statistics, and machine learning to extract and analyze the information related to railway costs infrastructure data. To validate the suggested approach, data from 23 real historical projects from the client network rail was extracted, allowing their costs to be comparable. Finally, some machine learning and data analytics methods were implemented to identify the most relevant factors allowing for costs benchmarking. The presented method proves the benefits of data extraction being able to gather, analyze and benchmark each project in an efficient manner, and deeply understand the relationships and the relevant factors that matter in infrastructure costs.
Keywords
data extraction; data mining; railway infrastructure costs; infrastructure costs data analysis; cost analysis
Subject
Engineering, Transportation Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
