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Regression-based algorithms for exploring the relationships in a cement

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dc.contributor.author Tutmez, B
dc.contributor.author Dag, A
dc.date.accessioned 2022-10-19T07:36:41Z
dc.date.available 2022-10-19T07:36:41Z
dc.date.issued 2012
dc.identifier.uri http://hdl.handle.net/11616/81222
dc.description.abstract Using appropriate raw materials for cement is crucial for providing the required products. Monitoring relationships and analyzing distributions in a cement material quarry are important stages in the process. CaO, one of the substantial chemical components, is included in some raw materials such as limestone and marl; furthermore, appraising spatial assessment of this chemical component is also very critical. In this study, spatial evaluation and monitoring of CaO concentrations in a cement site are considered. For this purpose, two effective regression-based models were applied to a cement quarry located in Turkey. For the assessment, some spatial models were developed and performance comparisons were carried out. The results show that the regression-based spatial modelling is an efficient methodology and it can be employed to evaluate spatially varying relationships in a cement quarry.
dc.description.abstract C1 [Tutmez, Bulent] Inonu Univ, Dept Min Engn, TR-44280 Malatya, Turkey.
dc.description.abstract [Dag, Ahmet] Cukurova Univ, Dept Min Engn, TR-01100 Adana, Turkey.
dc.source COMPUTERS AND CONCRETE
dc.title Regression-based algorithms for exploring the relationships in a cement
dc.title raw material quarry


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