Evaluating the performance of combining neural networks and genetic algorithms to forecast construction demand: The case of the Singapore residential sector

Construction Management and Economics

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Bibliographic Details
Main Author:	Bee-Hua, G.
Other Authors:	SCHOOL OF BUILDING & REAL ESTATE
Format:	Article
Published:	2013
Subjects:	Accuracy Construction demand Forecasting Genetic algorithms Neural networks
Online Access:	http://scholarbank.nus.edu.sg/handle/10635/46420
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-46420
record_format	dspace
spelling	sg-nus-scholar.10635-464202024-11-11T02:57:54Z Evaluating the performance of combining neural networks and genetic algorithms to forecast construction demand: The case of the Singapore residential sector Bee-Hua, G. SCHOOL OF BUILDING & REAL ESTATE Accuracy Construction demand Forecasting Genetic algorithms Neural networks Construction Management and Economics 18 2 209-217 CMECF 2013-10-16T02:01:20Z 2013-10-16T02:01:20Z 2000 Article Bee-Hua, G. (2000). Evaluating the performance of combining neural networks and genetic algorithms to forecast construction demand: The case of the Singapore residential sector. Construction Management and Economics 18 (2) : 209-217. ScholarBank@NUS Repository. 01446193 http://scholarbank.nus.edu.sg/handle/10635/46420 NOT_IN_WOS Scopus
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	Accuracy Construction demand Forecasting Genetic algorithms Neural networks
spellingShingle	Accuracy Construction demand Forecasting Genetic algorithms Neural networks Bee-Hua, G. Evaluating the performance of combining neural networks and genetic algorithms to forecast construction demand: The case of the Singapore residential sector
description	Construction Management and Economics
author2	SCHOOL OF BUILDING & REAL ESTATE
author_facet	SCHOOL OF BUILDING & REAL ESTATE Bee-Hua, G.
format	Article
author	Bee-Hua, G.
author_sort	Bee-Hua, G.
title	Evaluating the performance of combining neural networks and genetic algorithms to forecast construction demand: The case of the Singapore residential sector
title_short	Evaluating the performance of combining neural networks and genetic algorithms to forecast construction demand: The case of the Singapore residential sector
title_full	Evaluating the performance of combining neural networks and genetic algorithms to forecast construction demand: The case of the Singapore residential sector
title_fullStr	Evaluating the performance of combining neural networks and genetic algorithms to forecast construction demand: The case of the Singapore residential sector
title_full_unstemmed	Evaluating the performance of combining neural networks and genetic algorithms to forecast construction demand: The case of the Singapore residential sector
title_sort	evaluating the performance of combining neural networks and genetic algorithms to forecast construction demand: the case of the singapore residential sector
publishDate	2013
url	http://scholarbank.nus.edu.sg/handle/10635/46420
_version_	1821230109618601984

Evaluating the performance of combining neural networks and genetic algorithms to forecast construction demand: The case of the Singapore residential sector

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