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dc.contributor.authorWaheeb, Rasha A
dc.contributor.authorWheib, KA
dc.contributor.authorAndersen, Bjørn Sørskot
dc.contributor.authorAlsuhili, Rafea
dc.date.accessioned2023-01-13T12:38:44Z
dc.date.available2023-01-13T12:38:44Z
dc.date.created2022-09-04T09:54:24Z
dc.date.issued2022
dc.identifier.citationSocial Science Research Network (SSRN). 2022, .en_US
dc.identifier.issn1556-5068
dc.identifier.urihttps://hdl.handle.net/11250/3043377
dc.description.abstractCurrently and under the COVID-19 which is considered as a kind of disaster or even any other natural or manmade disasters, this study was confirmed to be important especially when the society is proceeding to recover and reduce the risks of as possible as injuries. These disasters are leading somehow to paralyze the activities of society as what happened in the period of COVID-19, therefore, more efforts were to be focused for the management of disasters in different ways to reduce their risks such as working from distance or planning solutions digitally and send them to the source of control and hence how most countries overcame this stage of disaster (COVID-19) and collapse. Artificial intelligence should be used when there is no practical solution for a problem occurring in a projects starting from individual self-development ending to the adaptation to information technology sector with a continuous posting in this world of information industry where as metaphor “needs is a cause of creativity”. This study focuses on the use of artificial neural networks ANN to find a solution to issues in projects delays and furthermore when there is no physical or mathematical solution found so far. ANN’s were used to build a model that helps in finding a solution for delays in some selected projects in Baghdad (as case study), and discussing the strategies of rebuilding plus delays in time and cost due to delay factors. 35 construction projects were chosen in Baghdad greater area, vary in sizes and types. Crew and laborers were targeted in sampling collection methodology basically throughout questionnaire forms of field survey as they were filled by them. ANN’s helped in modelling delays factors to help decision makers in an appropriate management of projects. External factors which includes disasters mentioning COVID-19 as the most important disaster ever happened in the last decades, were the most important factor that caused delay in time and cost of projects implementation processes where this factor was controlling the other major factors such as contractor failure, redesigning, changing orders, security issues, low prices, besides weather issues and owner failure.en_US
dc.language.isoengen_US
dc.publisherSocial Science Research Network (SSRN)en_US
dc.titleThe Prospective of Artificial Neural Network (ANN’s) Model Application to Ameliorate Management of Post Disaster Engineering Projectsen_US
dc.title.alternativeThe Prospective of Artificial Neural Network (ANN’s) Model Application to Ameliorate Management of Post Disaster Engineering Projectsen_US
dc.typeJournal articleen_US
dc.description.versionsubmittedVersionen_US
dc.source.pagenumber27en_US
dc.source.journalSocial Science Research Network (SSRN)en_US
dc.identifier.doihttp://dx.doi.org/10.2139/ssrn.4180813
dc.identifier.cristin2048598
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode0


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