Building a predictive model to improve the quality of government building construction projects in Iraq using Multi Linear Regression technique

Author:

ALFahham Ahmed F. H.,Alajeeli Hatem K. B.

Abstract

Abstract Quality measurement is an important tool for quality improvement. Due to the lack of tools and methods used to measure quality, quality improvement in construction projects is difficult. As a result of the high cost of construction projects for public buildings and the lack of improved tools for measuring quality, there is an urgent need to develop new models. This study aims to provide necessary information for owners, project managers, designers, and contractors to determine the main and secondary factors that have a major impact on improving the quality of construction projects for government buildings and reduce maintenance. This study also contributes to building a predictive model to measure the quality of these projects, and a literature review and interviews were conducted. A personal figure to collect a list of factors affecting the quality of government building projects, and the resulting factors were subject to a survey that was sent to owners, project managers, and engineers working on general construction projects in Iraq. Adoption of the technique of multiple linear regression in the modeling process and determining the most important factors that affect the quality of the project.

Publisher

IOP Publishing

Subject

General Medicine

Reference16 articles.

1. Framework for quality improvement of infrastructure projects;Warsame;Journal of Civil Engineering and Architecture,2013

2. Factors affecting the quality of building projects in Hong Kong;Chan;International Journal of Quality & Reliability Management,2000

3. Prediction of quality performance using artificial neural networks;Jha,2009

4. Ranking of key quality factors in the Indian construction industry;Shanmugapriya;International Research Journal of Engineering and Technology,2015

5. Assessment of factors affecting quality management in construction industry;Yenurkar;IJRESTs,2015

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3