Add to ORKGMethods like DBSCAN are widely used in the analysis of spatial data. These methods are based on the neighborhood relations which use distance between points. However, these neighborhood relations consider to have at least a certain number of neighbors within a definite boundary. In this proposed work such a neighborhood analysis is done by using the benefits of fuzzy sets theory. Usage of fuzzy logic gives more sensitive and realistic results. In this paper, Fuzzy Joint Points (FJP) based on this theory is handled and sonic theoretical properties used in neighborhood analysis are investigated
In this study, regional analysis based on a limited number of data, which is an important real probl...
We implement an algorithm that uses a system of fuzzy relation equations (SFRE) with the max-min com...
Geometric footprints, which delineate the region occupied by a spatial point pattern, serve a variet...
The aim of this paper has twofold: i) to explore the fundamental concepts and methods of neighborhoo...
Cluster analysis is one of the most crucial techniques in statistical data analysis. Among the clust...
In this paper, a new level-based (hierarchical) approach to the fuzzy clustering problem for spatial...
A new hierarchical approach to the problem of clustering, called the Fuzzy Joint Point, FJP) method ...
The present article considers the fuzzy joint points (FJP) method for the problem of fuzzy clusterin...
Using fuzzy neighborhood relations in density-based clustering, like in Fuzzy Joint Points (FJP) alg...
This study investigates whether a fuzzy clustering method is of any practical value in delineating u...
The paper deals with a special class of cluster analysis methods where a membership degree is calcul...
One of the most interesting and promising approaches to the analysis of multivariate phenomena and p...
The fuzzy joint points (FJP) method is one of the successful fuzzy approaches to density-based clust...
Abstract. The main purpose of this paper is to achieve improvement in the speed of Fuzzy Joint Point...
Day by day huge amounts data are produced, and evaluation of these data becomes more difficult. The ...
In this study, regional analysis based on a limited number of data, which is an important real probl...
We implement an algorithm that uses a system of fuzzy relation equations (SFRE) with the max-min com...
Geometric footprints, which delineate the region occupied by a spatial point pattern, serve a variet...
The aim of this paper has twofold: i) to explore the fundamental concepts and methods of neighborhoo...
Cluster analysis is one of the most crucial techniques in statistical data analysis. Among the clust...
In this paper, a new level-based (hierarchical) approach to the fuzzy clustering problem for spatial...
A new hierarchical approach to the problem of clustering, called the Fuzzy Joint Point, FJP) method ...
The present article considers the fuzzy joint points (FJP) method for the problem of fuzzy clusterin...
Using fuzzy neighborhood relations in density-based clustering, like in Fuzzy Joint Points (FJP) alg...
This study investigates whether a fuzzy clustering method is of any practical value in delineating u...
The paper deals with a special class of cluster analysis methods where a membership degree is calcul...
One of the most interesting and promising approaches to the analysis of multivariate phenomena and p...
The fuzzy joint points (FJP) method is one of the successful fuzzy approaches to density-based clust...
Abstract. The main purpose of this paper is to achieve improvement in the speed of Fuzzy Joint Point...
Day by day huge amounts data are produced, and evaluation of these data becomes more difficult. The ...
In this study, regional analysis based on a limited number of data, which is an important real probl...
We implement an algorithm that uses a system of fuzzy relation equations (SFRE) with the max-min com...
Geometric footprints, which delineate the region occupied by a spatial point pattern, serve a variet...