東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Construction analytics = forecasting...

Shahandashti, Mohsen.

Linked to FindBook

Google Book

Amazon

博客來

Construction analytics = forecasting and investment valuation /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Construction analytics/ by 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.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Construction industry - Statistical methods. -
Online resource:	https://doi.org/10.1007/978-3-031-27292-9
ISBN:	9783031272929

Construction analytics = forecasting 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

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

3631700
Construction industry
--Statistical methods.

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

Dewey Class. No.: 338.47624

Construction analytics = forecasting and investment valuation /
LDR:02937nmm a2200337 a 4500 001 2317532
003 DE-He213
005 20230424143901.0
006 m d
007 cr nn 008maaau
008 230902s2023 sz s 0 eng d
020 $a 9783031272929 $q (electronic bk.)
020 $a 9783031272912 $q (paper)
024 7 $a 10.1007/978-3-031-27292-9 $2 doi
035 $a 978-3-031-27292-9
040 $a GP $c GP
041 0 $a eng
050 4 $a HD9715.A2 $b S53 2023
072 7 $a TN $2 bicssc
072 7 $a KJM $2 bicssc
072 7 $a TEC005000 $2 bisacsh
072 7 $a TNT $2 thema
082 0 4 $a 338.47624 $2 23
090 $a HD9715.A2 $b C758 2023
245 0 0 $a Construction analytics $h [electronic resource] : $b forecasting and investment valuation / $c by Mohsen Shahandashti ... [et al.].
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2023.
300 $a viii, 186 p. : $b ill., digital ; $c 24 cm.
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.
650 0 $a Construction industry $x Statistical methods. $3 3631700
650 0 $a Construction industry $x Management $x Data processing. $3 913859
650 0 $a Time-series analysis. $3 532530
650 0 $a R (Computer program language) $3 784593
650 1 4 $a Construction Management. $3 896611
650 2 4 $a Building Construction and Design. $3 3166685
650 2 4 $a Building Materials. $3 894213
650 2 4 $a Investment Appraisal. $3 2191345
650 2 4 $a Civil Engineering. $3 891037
700 1 $a Shahandashti, Mohsen. $3 3631699
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-27292-9
950 $a Engineering (SpringerNature-11647)