Yazar "Yuceer M." seçeneğine göre listele

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    An interactive gis-based software for dynamic monitoring of rivers
    (Scibulcom Ltd., 2014) Yetik M.K.; Yuceer M.; Karadurmus E.; Semizer E.; Calimli A.; Berber R.
    Water quality research and development attempts have been the most valuable resources in the sense of model calibration and verification techniques. Due to the fact that current degree of pollution in rivers and importance of the sustainable water resources management, the interactive river monitoring becomes inevitable. Within the scope of river water quality monitoring, Geographical Information Systems (GIS) are gaining widespread acceptance besides this fast and reliable water quality models and parameter estimation techniques are becoming available. However, integrating water quality models with GIS is limited in literature. This study presents an integrated platform on which ArcMap as a GIS and a water quality model in MATLAB are brought together in an interactive and user friendly manner. The software provides a considerable developments in future real time river monitoring and environmental pollution assessment.
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    Modeling of blending of mineral base oils via artificial neural networks
    (Czech Society of Chemical Engineering, 2014) Karadurmus E.; Akyazi H.; Yuceer M.
    [No abstract available]
  • Küçük Resim Yok
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    Modeling water quality in rivers: A case study of Beylerderesi river in Turkey
    (Corvinus University of Budapest, 2016) Yuceer M.; Coskun M.A.
    River pollution is a major environmental problem that has negative consequences for humans and wildlife alike. To prevent its consequences, the sources and severity of pollution must be determined by monitoring water quality in river basins, followed by the measures necessary to control the contamination. Models and computer simulation of water quality are important tools for predicting adverse effects of pollution along a stream, and they can help guide practical investments in stream health. In water quality models, parameters that are determined through optimization rather than through trial and error are required to ensure the reliability of the model. In this study, a continuous stirred tank reactor (CSTR) approach was used to model Beylerderesi stream as a dynamic model, and the kinetic parameters were determined through optimization. For the optimization step, the Sequential Quadratic Programming method was used. The model predictions indicated good agreement with experimental data. The Mean Absolute Percentage error values for dissolved oxygen and biochemical oxygen demand were calculated as 0.95% and 1.39%, respectively. Statistical analysis showed differences between river and effluent samples for all parameters measured. © 2016, ALÖKI Kft., Budapest, Hungary.