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Construction analyticsforecasting and investment valuation /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Construction analyticsby Mohsen Shahandashti ... [et al.].
Reminder of title:	forecasting and investment valuation /
other author:	Shahandashti, Mohsen.
Published:	Cham :Springer Nature Switzerland :2023.
Description:	viii, 186 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Construction industryStatistical methods.
Online resource:	https://doi.org/10.1007/978-3-031-27292-9
ISBN:	9783031272929$q(electronic bk.)

Construction analyticsforecasting and investment valuation /
Construction analyticsforecasting and investment valuation /[electronic resource] :by Mohsen Shahandashti ... [et al.]. - Cham :Springer Nature Switzerland :2023. - viii, 186 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9783031272929$q(electronic bk.)

Standard No.: 10.1007/978-3-031-27292-9doiSubjects--Topical Terms:

950577
Construction industry
--Statistical methods.

LC Class. No.: HD9715.A2 / S53 2023

Dewey Class. No.: 338.47624

Construction analyticsforecasting and investment valuation /
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505 0 $a 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.
520 $a 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.
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