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Öğe Bulanık modelleme yaklaşımının tenör kestiriminde kullanılması(2006) Tütmez, Bülent; Tercan, A. ErhanÖz: Tenör kestirimi madencilik yatırım ve projelerinin geliştirilmesinde büyük bir önem taşır. Bu çalışmada tenör kestirimine bulanık mantık yaklaşımı tanıtılmış ve yaklaşım Karsantı (Adana) krom yatağından elde edilen verilere uygulanmıştır. Uygulamada Takagi-Sugeno tipi bulanık modelleme yordamı kullanılmıştır. Bulanık model, sırasıyla verilerin kümelenmesi, kural sisteminin oluşturulması ve parametre optimizasyonu aşamalarını izlemektedir. Esnek ve şeffaf bir model yapısı kullanılarak elde edilen kestirim değerleri ölçülen tenör değerleri ile karşılaştırılmış ve kestirimlerin başarısı test edilmiştir.Öğe Evaluating geo-environmental variables using a clustering based areal model(Pergamon-Elsevier Science Ltd, 2012) Tutmez, Bulent; Kaymak, Uzay; Tercan, A. Erhan; Lloyd, Christopher D.Global regression models do not accurately reflect the spatial heterogeneity which characterises most geo-environmental variables. In analysing the relationships between such variables, an approach is required which allows the model parameters to vary spatially. This paper proposes a new framework for exploring local relationships between geo-environmental variables. The method is based on extended objective function based fuzzy clustering with the environmental parameters estimated through on a locally weighted regression analysis. The case studies and prediction evaluations show that the fuzzy algorithm yields well-fitted models and accurate predictions. In addition to an increased accuracy of prediction relative to the widely-used geographically weighted regression (GWR), the proposed algorithm provides the search radius (bandwidth) and weights for local estimation directly from the data. The results suggest that the method could be employed effectively in tackling real world kernel-based modelling problems. (C) 2012 Elsevier Ltd. All rights reserved.Öğe Local models for the analysis of spatially varying relationships in a lignite deposit(European Soc Fuzzy Logic & Technology, 2009) Tutmez, Bulent; Tercan, A. Erhan; Kaymak, Uzay; Lloyd, Christopher D.Relationships between geographically referenced variables are usually spatially heterogeneous and, to account for such variations, local models are necessary. This paper compares the Geographically Weighted Regression (GWR) model, usually used to integrate and examine the spatial heterogeneity of a relationship, and the Fuzzy Clustering-Based Least Squares (FCBLS) model for the analysis of spatially varying relationships. Both models use the same model parameters and bandwidth values derived from the Akaike Information Criterion. The results show that FCBLS outperforms the GWR model.Öğe Local spatial regression models: a comparative analysis on soil contamination(Springer, 2012) Tutmez, Bulent; Kaymak, Uzay; Tercan, A. ErhanSpatial data analysis focuses on both attribute and locational information. Local analyses deal with differences across space whereas global analyses deal with similarities across space. This paper addresses an experimental comparative study to analyse the spatial data by some weighted local regression models. Five local regression models have been developed and their estimation capacities have been evaluated. The experimental studies showed that integration of objective function based fuzzy clustering to geostatistics provides some accurate and general models structures. In particular, the estimation performance of the model established by combining the extended fuzzy clustering algorithm and standard regional dependence function is higher than that of the other regression models. Finally, it could be suggested that the hybrid regression models developed by combining soft computing and geostatistics could be used in spatial data analysis.
