Computers and Concrete

  • 제10권5호
  • /
  • Pages.457-467
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  • 2012
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  • 1598-8198(pISSN)
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  • 1598-818X(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

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Regression-based algorithms for exploring the relationships in a cement raw material quarry

  • Tutmez, Bulent (Department of Mining Engineering, Inonu University) ;
  • Dag, Ahmet (Department of Mining Engineering, Cukurova University)
  • 투고 : 2011.07.11
  • 심사 : 2012.05.10
  • 발행 : 2012.11.25
⟨ 이전 논문 다음 논문 ⟩

초록

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.

키워드

참고문헌

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피인용 문헌

  1. Analyzing non-stationarity in cement stone pit by median polish interpolation: a case study vol.41, pp.2, 2014, https://doi.org/10.1080/02664763.2013.840274
  2. Lithological classification of cement quarry using discriminant algorithms vol.26, pp.3, 2012, https://doi.org/10.1007/s11771-019-4042-6
  3. Machine learning-driven new material discovery vol.2, pp.8, 2020, https://doi.org/10.1039/d0na00388c