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Book Cover
E-book
Author Shahandashti, Mohsen, author

Title Construction analytics : forecasting and investment valuation / Mohsen Shahandashti, Bahram Abediniangerabi, Ehsan Zahed, Sooin Kim
Published Cham : Springer, 2023

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Description 1 online resource (viii, 186 pages)
Contents Chapter 1. Introduction to Construction Analytics -- Chapter 2. Construction Forecasting using Univariate Time Series Models -- Chapter 3. Construction Forecasting Using Time-series Volatility Models -- Chapter 4. Construction Forecasting using Multivariate Time Series Models -- Chapter 5. Construction Forecasting Using Recurrent Neural Networks -- Chapter 6. Investment Valuation of Construction Projects Under Uncertainty -- Appendices: Construction time series datasets, including National Highway Construction Cost Index (NHCCI), Federal Highway Construction Spending, Iowa Highway Construction
Summary This text covers R program coding for the implementation of two essential data analytics for practical construction problems. The first part of this book explains time series basics, models, and forecasting approaches in the context of the construction industry, accompanied by practical examples in construction. The second part describes the concept of investment valuation for construction projects and provides both deterministic and probabilistic techniques to conduct investment valuation on construction projects. R code scripts are provided in this book for solving practical problems in the construction industry. This book is also equipped with an R Package entitled "cdar" to provide the necessary functions for performing investment valuation. The book maximizes students' understanding of the necessary theoretical background of data analytics, and explains the implementation of data analytics techniques to solve the actual problems in the construction industry. Illustrates theoretical explanations of construction analytics, hands-on practices, and R codes for analytics techniques; Enables readers to investigate the problems in the construction industry such as cost overruns and investment timing; Reinforces concepts presented with problems and solutions, datasets, and programming codes
Bibliography Includes bibliographical references and index
Notes Online resource; title from PDF title page (SpringerLink, viewed May 3, 2023)
Subject Construction industry -- Statistical methods.
Construction industry -- Management -- Data processing
Time-series analysis.
R (Computer program language)
Construction industry -- Management -- Data processing
Construction industry -- Statistical methods
R (Computer program language)
Time-series analysis
Form Electronic book
Author Abediniangerabi, Bahram, author
Zahed, Ehsan, author
Kim, Sooin, author
ISBN 9783031272929
3031272927