Midlands State University Library

Artificial neural network cost flow risk assessment model (Record no. 165891)

MARC details
000 -LEADER
fixed length control field 02439nam a22002657a 4500
003 - CONTROL NUMBER IDENTIFIER
control field ZW-GwMSU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240604132823.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240604b |||||||| |||| 00| 0 eng d
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 01446193
040 ## - CATALOGING SOURCE
Original cataloging agency MSU
Language of cataloging English
Transcribing agency MSU
Description conventions rda
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number HD9715.A1 CON
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Odeyinka, Henry A.
Relator term co-author
245 10 - TITLE STATEMENT
Title Artificial neural network cost flow risk assessment model
Statement of responsibility, etc. created by Henry A. Odeyinka,John Lowe and Ammar P. Kaka
264 1# - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Abingdon:
Name of producer, publisher, distributor, manufacturer Taylor and Francis,
Date of production, publication, distribution, manufacture, or copyright notice 2013
336 ## - CONTENT TYPE
Source rdacontent
Content type term text
Content type code txt
337 ## - MEDIA TYPE
Source rdamedia
Media type term unmediated
Media type code n
338 ## - CARRIER TYPE
Source rdacarrier
Carrier type term volume
Carrier type code nc
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Construction Management and Economics
Volume/sequential designation Volume 31, number 4-6
520 3# - SUMMARY, ETC.
Summary, etc. Previous attempts have been made to model cash flow forecast at the tender stage using net cash flow, value flow and cost flow approaches. Despite these efforts, significant variations between the actual and modelled forecasts were still observable. The main cause identified is the issue of risk inherent in construction. Using the cost flow approach, a model is developed to assess the impacts of risk occurring during the construction stage on the initial forecast cost flow. A questionnaire survey and case study approach were employed. As a first step, a questionnaire survey was administered to UK construction contractors to determine the significant risk factors impacting on their cost flow forecast. Using mean ranking analysis, the survey yielded 11 significant risk factors. The second stage of data collection involves the collection of forecast and actual cost flow data from case study projects to establish their variations at predetermined time periods. Using the significant risk factors identified in the first phase, relevant construction professionals who worked on the case study projects were requested to score the extent of risk occurrence that resulted in the observed variations. A combination of these two sets of data was used to model the impact of risk on cost flow forecast using an artificial neural network back propagation algorithm. The model enables a contractor to predict the likely changes to a cost flow profile due to risks occurring in the construction stage.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Artificial neural network
Form subdivision Contractor
General subdivision Cost flow forecasting
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Lowe, John
Relator term co-author
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Kaka, Ammar P
Relator term co-author
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1080/01446193.2013.802363
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Journal Article
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Serial Enumeration / chronology Total Checkouts Full call number Date last seen Copy number Price effective from Koha item type Public note
    Library of Congress Classification     Main Library Main Library - Special Collections 15/01/2014 Vol. 31, no. 4-9 (pages 423-439)   HD9715.A1 CON 04/06/2024 SP18033 04/06/2024 Journal Article For in house use