<?xml version="1.0" encoding="utf-8"?>
<journal>
<title>International Journal of Civil Engineering</title>
<title_fa>مجله بین المللی مهندسی عمران</title_fa>
<short_title>IJCE</short_title>
<subject>Engineering &amp; Technology</subject>
<web_url>http://ijce.iust.ac.ir</web_url>
<journal_hbi_system_id>18</journal_hbi_system_id>
<journal_hbi_system_user>agent2</journal_hbi_system_user>
<journal_id_issn>1735-0522</journal_id_issn>
<journal_id_issn_online>2283-3874</journal_id_issn_online>
<journal_id_pii></journal_id_pii>
<journal_id_doi></journal_id_doi>
<journal_id_iranmedex></journal_id_iranmedex>
<journal_id_magiran></journal_id_magiran>
<journal_id_sid></journal_id_sid>
<journal_id_nlai></journal_id_nlai>
<journal_id_science></journal_id_science>
<language>en</language>
<pubdate>
	<type>jalali</type>
	<year>1392</year>
	<month>9</month>
	<day>1</day>
</pubdate>
<pubdate>
	<type>gregorian</type>
	<year>2013</year>
	<month>12</month>
	<day>1</day>
</pubdate>
<volume>11</volume>
<number>4</number>
<publish_type>online</publish_type>
<publish_edition>1</publish_edition>
<article_type>fulltext</article_type>
<articleset>
	<article>


	<language>en</language>
	<article_id_doi></article_id_doi>
	<title_fa></title_fa>
	<title>Predicting the operation and maintenance costs of condominium properties in the project planning phase: An artificial neural network approach</title>
	<subject_fa>Construction Management</subject_fa>
	<subject>Construction Management</subject>
	<content_type_fa>Research Paper</content_type_fa>
	<content_type>Research Paper</content_type>
	<abstract_fa></abstract_fa>
	<abstract>The decisions made in the planning phase of a building project greatly affect its future operation and maintenance (O&amp;M) 
cost. Recognizing the O&amp;M cost of condominiums’ common facilities as a critical issue for home owners, this research aims to 
develop  an  artificial  neural  network  (ANN)  O&amp;M  cost  prediction  model  to  assist  developers  and  architects  in  effectively 
assessing  the  impacts  of  their  decisions  made  in  the  planning  phase  of  condominium  projects  on  future  O&amp;M  costs.  A 
regression  cost  prediction  model  was  also  developed  as  a  benchmark  model  for  testing  the  predictive  accuracy  of  the  ANN 
model. Six critical building design attributes (building age, number of apartment units, number of floors, average sale price, 
total floor area, and common facility floor area) which are usually available in the project planning phase, were identified as 
the  input  factors  to  both  models  and  average  monthly  O&amp;M  cost  as  the  output  factor.  55  of  the  65  existing  condominium 
properties randomly selected were treated as the training samples whose data were used to develop the ANN and regression 
models the other ten as the test samples to compare and verify the predictive performance of both models. The study results 
revealed  that  the  ANN  model  delivers  more  accurate  and  reliable  cost  prediction  results,  with  lower  average  absolute  error 
around 7.2% and maximum absolute error around 16.7%, as compared with the regression model. This study shows that ANN 
is an effective method in predicting building O&amp;M costs in the project planning phase. 
Keywords: Project management, Facility management, Common facilities, Cost modeling. 
</abstract>
	<keyword_fa></keyword_fa>
	<keyword>Project management, Facility management, Common facilities, Cost modeling</keyword>
	<start_page>242</start_page>
	<end_page>250</end_page>
	<web_url>http://ijce.iust.ac.ir/browse.php?a_code=A-10-852-1&amp;slc_lang=en&amp;sid=1</web_url>


<author_list>
	<author>
	<first_name>K. J.</first_name>
	<middle_name></middle_name>
	<last_name>Tu</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>kjtu@mail.ntust.edu.tw</email>
	<code>180031947532846005749</code>
	<orcid>180031947532846005749</orcid>
	<coreauthor>Yes
</coreauthor>
	<affiliation>National Taiwan University of Science and Technology</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Y. W.</first_name>
	<middle_name></middle_name>
	<last_name>Huang</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>hcra@hotmail.com</email>
	<code>180031947532846005750</code>
	<orcid>180031947532846005750</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>National Taiwan University of Science and Technology</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


</author_list>


	</article>
</articleset>
</journal>
