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Öğe An algorithm for quantifying regionalized ore grades(South African Inst Mining Metallurgy, 2008) Tutmez, B.; Tercan, A. E.; Kaymak, U.We present a novel, hybrid algorithm for quantifying the ore grade variability that has central importance in ore reserve estimation. The proposed algorithm has three stages: (1) fuzzy clustering, (2) similarity measure, and (3) grade estimation. The method first considers data clustering, and then uses the clustering information for quantifying the ore grades by means of a cumulative point semimadogram function. The method provides a measure of similarity and gives an indication of the regional heterogeneity. In addition, grade estimations can be obtained at different levels of similarity using a weighting function, which is the standard regional dependence function (SRDF).Öğe Evaluation of Mn concentration provided by soil in citrus-growing regions(Elsevier Sci Ltd, 2009) Tutmez, B.; Dag, A.; Erdem, H.; Torun, B.Manganese (Mn) is an essential nutrient element in citrus growing and Mn deficiency causes some problems related with physiological and morphological structure. Spatial evaluation of Mn obtained from soils in citrus-growing areas is the main objective of this paper. For this purpose, a citrus-growing region in Turkey has been selected and three effective estimation methods: kriging, neural-fuzzy modelling, and fuzzy interval arithmetic have been considered for the spatial evaluations. The model works primarily focus on the model accuracy and smoothing degree of estimations. In addition, error analysis and comparative assessments, which present the advantages and drawbacks of the models, are conducted in the paper. The results and performance evaluations prove the superiorities of soft computing approach in this evaluation. (C) 2009 Elsevier B.V. All rights reserved.Öğe A linguistic model for evaluating cement strength(Springer, 2009) Tutmez, B.; Dag, A.This paper presents a soft methodology for predicting the 28-day compressive strength of Portland cement (CCS) by making use of the 1-day, 3-day and 7-day CCS values. Data taken from a cement plant in Turkey have been employed in the model construction and testing. For implementation, linguistic models were designed based on if-then fuzzy rules. In addition, predictions of these models were compared with results of the regression models. The performance evaluations showed that the linguistic-based fuzzy predictions are very satisfactory in estimating cement strength and the linguistic modeling performs better than regression modeling.Öğe Measuring Dependence between Calorific Values of Lignite and Spatial Positions by Rank Correlation Method: A Case Study(Taylor & Francis Inc, 2010) Tutmez, B.; Dag, A.; Cengiz, A. K.This article presents an investigation for evaluating the relationship between calorific value of lignite and its spatial position using non parametric statistics. Measuring dependence between calorific values and spatial positions is important for production planning and making decisions. For this purpose, a three dimensional data set (easting-x, northing-y, and elevation-z) obtained from Afsin-Elbistan lignite deposit is employed. Rank correlation measurements have been carried out between spatial dimensions and calorific values. In addition, the significances of rank correlation coefficients have been appraised using hypothesis tests. As a result of the study, a strong rank correlation between y and calorific values and a weak rank correlation between z and calorific values are observed, respectively. On the other hand, very low-rank correlation between coordinate x and calorific values is measured for the deposit.Öğe Uncertainty-Based Analysis for Agreement of Tensile-Strength Measurement Procedures(Amer Soc Testing Materials, 2017) Tutmez, B.; Unver, B.Rocks fail because of compression, shear, tensile and/or a combination of these stresses. Rocks are more vulnerable to tensile stresses as they can stably accommodate only a fraction of compressive stresses in tensional loading. Therefore, reliable determination of tensile strength of rocks is important. Tensile strength of rocks that can be determined by both direct and indirect tensile testing methods have great importance in rock mechanics. Although these methods have different procedures and quite a change in results, an agreement between the methods is necessary. In addition, properly appraising the data provided by direct and indirect measurements has critical importance for applying the knowledge thereby acquired. From this point, based on the conventional measurement uncertainty framework, two weighting methods are suggested to combine the tensile strength methods. Thus, an uncertainty-based agreement between the direct and indirect tensile-strength measurements has been made. The results showed that the weighted uncertainties of the proposed methods are lower than the best single measurement uncertainties. In addition, the weighted averages and corresponding uncertainties provide additional information and unique outcomes for the users. A reliable correlation between indirect and direct tensile-strength results is certainly useful for assessing tensile strength of rocks.Öğe Use of hybrid intelligent computing in mineral resources evaluation(Elsevier Science Bv, 2009) Tutmez, B.Mineral resources are a formal quantification of naturally occurring materials. Estimation of resource parameters such as grade and thickness may be carried out using different methodologies. In this paper, a soft methodology, which is artificial neural network (ANN) based fuzzy modelling is presented for grade estimation and its stages are demonstrated. The neuro-fuzzy method uses preliminary clustering and finally estimates the ore grades based on radial basis neural network and interpolation. Two case studies designed for both simulated and real data sets indicate that the approach is relatively accurate and flexible. In addition, the method is suitable for modelling via limited number of data. The results and performance comparisons with conventional methods show that the computing method is efficient. (C) 2009 Elsevier B.V. All rights reserved.
