Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/5071
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dc.contributor.advisorSemaan, Nabilen_US
dc.contributor.authorAlam, Elise Alen_US
dc.date.accessioned2021-06-11T08:40:29Z-
dc.date.available2021-06-11T08:40:29Z-
dc.date.issued2021-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/5071-
dc.descriptionIncludes bibliographical references (p. 31-33)en_US
dc.description.abstractA contractor planning to excavation jobs is a very unpredictable operation. How many excavation jobs a contractor can perform in a specific period remains uncertain. The number of excavation jobs per a certain period is a purely stochastic problem, and is affected by lot of uncertain events. Thus, this project models the excavation operation using Markov Chains. the Markov Chain develops probability matrices that predicts a stochastic number of excavation jobs per month. Data were collected from sixteen different sites and mainly used to estimate the probability of duration required to excavate a specific area. Probability distribution of the excavation durations per area of excavation are developed. Then the probabilities were used to develop the Markov Chain transition matrices. Finally plots of prediction curves are developed. This project helps contractors plan their excavation work load for a period of time.en_US
dc.description.statementofresponsibilityby Elise Al Alamen_US
dc.format.extent1 online resource (vii, 33 pages) ; ill., tablesen_US
dc.language.isoengen_US
dc.rightsThis object is protected by copyright, and is made available here for research and educational purposes. Permission to reuse, publish, or reproduce the object beyond the personal and educational use exceptions must be obtained from the copyright holderen_US
dc.subjectMarkov chain, excavation, number of excavating jobs, probability distributionen_US
dc.subject.lcshMarkov processesen_US
dc.subject.lcshDissertations, Academicen_US
dc.subject.lcshUniversity of Balamand--Dissertationsen_US
dc.titleEstimation of the number of excavating jobs using Markov chainen_US
dc.typeProjecten_US
dc.contributor.corporateUniversity of Balamanden_US
dc.contributor.departmentDepartment of Civil Engineeringen_US
dc.contributor.facultyFaculty of Engineeringen_US
dc.contributor.institutionUniversity of Balamanden_US
dc.date.catalogued2021-06-11-
dc.description.degreeMS in Civil Engineeringen_US
dc.description.statusPublisheden_US
dc.identifier.ezproxyURLhttp://ezsecureaccess.balamand.edu.lb/login?url=http://olib.balamand.edu.lb/projects_and_theses/289638.pdfen_US
dc.identifier.OlibID289638-
dc.provenance.recordsourceOliben_US
Appears in Collections:UOB Theses and Projects
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