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المؤلفTawo, E. E.
تاريخ الإتاحة2009-11-25T13:02:45Z
تاريخ النشر1999
اسم المنشورEngineering Journal of Qatar University
الاقتباسEngineering Journal of Qatar University, 1999, Vol. 12, Pages 125-149.
معرّف المصادر الموحدhttp://hdl.handle.net/10576/7804
الملخصIn all mining estimation techniques data play a very important role. Insufficient data would mean the quality of the estimate is unreliable. Due to the importance attached to a good and representative data set, the application of Geostatistics to the mining industry puts data before any model. Obtaining a good data set which is usually from drillhole samples is an expensive experiment besides the economic constraint usually placed on the amount of data which can be collected particularly at an early stage of a mineral development. The advent of a novel technique in 'Artificial Neural Network' (ANN) and its application to the minerals industry is compared with a tested geostatistical technique. Both techniques are presented and tested on a Bauxite deposit. The effectiveness of ANN as a cost saving technique is appraised
اللغةen
الناشرQatar University
الموضوعEngineering: Research Papers
العنوانA Comparison Between Artificial Neural Network And A Geostatistical Technique In The Estimation Of Regionalized Variables
النوعArticle
الصفحات125-149
رقم المجلد12
dc.accessType Open Access


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