Computational Technology Resources - CCP

A.H. Boussabaine, R. Thoms and T.M.S. Elhag

School of Architecture and Building Engineering, The University of Liverpool, Liverpool, United Kingdom

doi:10.4203/ccp.50.9.1

A.H. Boussabaine, R. Thoms, T.M.S. Elhag, "A Neural Network Model for Predicting Cost-Flow for Water Industry Projects", in B.H.V. Topping, M.B. Leeming, (Editors), "Innovation in Computer Methods for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 113-119, 1997. doi:10.4203/ccp.50.9.1

Abstract

This paper explains the need for cost-flow forecasting in water industry projects and investigates the methods currently used to perform such a task. The paper also introduces neural network as an alternative approach to existing methods. The method used to model the system is described. The relationship between the number of nodes used and the accuracy of the neural network in modelling the cost-flow is closely examined. An optimal solution is proposed for the case and a prototype system is described. The results of the investigation of the number of nodes used and testing of the prototype neural network for sample cases are presented and discussed.

purchase the full-text of this paper (price £20)

go to the previous paper
go to the next paper
return to the table of contents
return to the book description
purchase this book (price £52 +P&P)

	Computational & Technology Resources an online resource for computational, engineering & technology publications
	not logged in - login
Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 50 INNOVATION IN COMPUTER METHODS FOR CIVIL AND STRUCTURAL ENGINEERING Edited by: B.H.V. Topping and M.B. Leeming Paper IX.1 A Neural Network Model for Predicting Cost-Flow for Water Industry Projects A.H. Boussabaine, R. Thoms and T.M.S. Elhag School of Architecture and Building Engineering, The University of Liverpool, Liverpool, United Kingdom doi:10.4203/ccp.50.9.1 purchase the full-text of this paper Full Bibliographic Reference for this paper A.H. Boussabaine, R. Thoms, T.M.S. Elhag, "A Neural Network Model for Predicting Cost-Flow for Water Industry Projects", in B.H.V. Topping, M.B. Leeming, (Editors), "Innovation in Computer Methods for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 113-119, 1997. doi:10.4203/ccp.50.9.1 Abstract This paper explains the need for cost-flow forecasting in water industry projects and investigates the methods currently used to perform such a task. The paper also introduces neural network as an alternative approach to existing methods. The method used to model the system is described. The relationship between the number of nodes used and the accuracy of the neural network in modelling the cost-flow is closely examined. An optimal solution is proposed for the case and a prototype system is described. The results of the investigation of the number of nodes used and testing of the prototype neural network for sample cases are presented and discussed. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £52 +P&P)
Back to top	©Civil-Comp Limited 2023 - terms & conditions