Pattern recognition on seismic data is a useful technique for generating seismic facies maps that capture changes in the geological depositional setting. Seismic facies analysis can be performed using the supervised and unsupervised pattern recognition methods. Each of these methods has its own advantages and disadvantages. In this paper, we compared and evaluated the capability of two unsuperv...

in this research, the framework is presented for unsupervised change detection using multitemporal sar images based on integration clustering and level set methods. spatial correlation between pixels were considered by using contextual information. also as proposed method was used integration of gustafson-kessel clustering techniques (gkc) and level set methods for change detection. using clust...

Indonesia is a country that has population density increasing every year, with the increase in density, crime rate increasing. Criminal acts arise because they are supported by factors cause crime. To improve security and welfare of Indonesian people, authors grouped each province based on influence This study uses comparison Fuzzy C-Means Clustering (FCM) Gustafson-Kessel (FGK) methods using v...

Most of the techniques on identifying fault location depend on parameters of power transmission line. Thus, a complex mathematical solution will be considered which at such conditions, the dependence on line parameters will limit performance of algorithms. An independent or parameters free algorithm is an option to overcome this problem by using an artificial intelligent technique. This paper p...

In this paper wk have used two fuzzy clustering algorithms, namely Fuzzy C-Means (FCM) and Gustafson Kessel Clustering (GKC) for unsupervised change detection in multitemporal remote sensing images. In conventional FCM & GKC no spatio-contextual information is taken into account and thus the result is not so much robust to noise/outliers. By incorporation of local neighborhood informationthe pe...

With advances technologies of Internet and new digital image, the volume of digital images produced by scientific, educational, medical, industrial, and other applications has increased dramatically. The paper was inspired by symmetrical study about an image and also we tried to apply edge detection using Phase Congruency method that proposed by Kovesi. We tried making comparative study on edge...

We explore an approach to possibilistic fuzzy clustering that avoids a severe drawback of the conventional approach, namely that the objective function is truly minimized only if all cluster centers are identical. Our approach is based on the idea that this undesired property can be avoided if we introduce a mutual repulsion of the clusters, so that they are forced away from each other. We deve...

A Fick’s model that includes a Takagi-Sugeno fuzzy model to estimate the effective diffusivity was analyzed. The modelling of drying kinetics on mango trough this diffusional-fuzzy model was compared with the theoretical Fick’s model and the empirical Peleg and Weibull models. The identification and validation was performed from experimental drying curves of ripe mango slices (Mangifera indica ...

Two extensions to the objective function-based fuzzy clustering are proposed. First, the (point) prototypes are extended to hypervolumes, whose size can be fixed or can be determined automatically from the data being clustered. It is shown that clustering with hypervolume prototypes can be formulated as the minimization of an objective function. Second, a heuristic cluster merging step is intro...