Integration of Monte Carlo simulation and chi-square automatic interaction detector algorithm for modelling and estimation of conventional power plant construction volumes
Ali Azadeh,
Monireh Jalili and
Mohammad Abdollahi
International Journal of Services and Operations Management, 2014, vol. 19, issue 1, 83-102
Abstract:
This study presents an integrated approach based on chi-square automatic interaction detector (CHAID) algorithm, computer simulation and statistical tools for optimum modelling and estimation of power plant construction volumes. In this context, modelling applications in estimation of structural volumes in power plants is described. The required information for cabling volumes such as low-pressure and cable platter are collected from an actual power plant construction company. Since some of these projects cannot respond to essential data volume for modelling, Monte Carlo simulation method is used in this study to generate the required data. Moreover, based on existing information and experts' judgement, sufficient data will be generated. Then, using the simulated data, CHAID is introduced and used for estimation of construction volumes. This is the first study that integrates simulation and CHAID for optimum modelling of conventional power plant construction volumes.
Keywords: conventional power plants; Monte Carlo simulation; chi-square automatic interaction detector; CHAID; estimation; modelling; power plant construction; structural volumes; construction volumes. (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=64035 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijsoma:v:19:y:2014:i:1:p:83-102
Access Statistics for this article
More articles in International Journal of Services and Operations Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().