نتایج جستجو برای: kessel clustering algorithm
تعداد نتایج: 824731 فیلتر نتایج به سال:
Segmentation method for subject processing the multispectral satellite images based on fuzzy clustering and preliminary non-linear filtering is represented. Three fuzzy clustering algorithms, namely Fuzzy C-means, GustafsonKessel, and Gath-Geva have been utilized. The experimental results obtained using these algorithms with and without preliminary nonlinear filtering to segment multispectral L...
clustering is the process of dividing a set of input data into a number of subgroups. the members of each subgroup are similar to each other but different from members of other subgroups. the genetic algorithm has enjoyed many applications in clustering data. one of these applications is the clustering of images. the problem with the earlier methods used in clustering images was in selecting in...
wireless sensor networks (wsns) consist of a large number of sensor nodes which are capable of sensing different environmental phenomena and sending the collected data to the base station or sink. since sensor nodes are made of cheap components and are deployed in remote and uncontrolled environments, they are prone to failure; thus, maintaining a network with its proper functions even when und...
The clustering problem under the criterion of minimum sum of squares is a non-convex and non-linear program, which possesses many locally optimal values, resulting that its solution often being stuck at locally optimal values and therefore cannot converge to global optima solution. In this paper, we introduce several new variation operators for the proposed hybrid genetic algorithm for the cl...
Here, an algorithm is presented for solving the minimum sum-of-squares clustering problems using their difference of convex representations. The proposed algorithm is based on an incremental approach and applies the well known DC algorithm at each iteration. The proposed algorithm is tested and compared with other clustering algorithms using large real world data sets.
1.1. Problem definition: Neuro-Fuzzy Approach in Electrical Load Forecasting Modeling and identification of electrical load processes are essential for the operation and also planning of a utility either for a company or for a country. Electrical load forecasting is needed because people intend to make important decision on generating power generators, load switching, purchasing strategy and al...
Introduction: Clustering of human brain is a very useful tool for diagnosis, treatment, and tracking of brain tumors. There are several methods in this category in order to do this. In this study, modified balanced iterative reducing and clustering using hierarchies (m-BIRCH) was introduced for brain activation clustering. This algorithm has an appropriate speed and good scalability in dealing ...
Clustering techniques are used to extract the structure of software for understanding, maintaining, and refactoring. In the literature, most of the proposed approaches for software clustering are divided into hierarchical algorithms and search-based techniques. In the former, clustering is a process of merging (splitting) similar (non-similar) clusters. These techniques suffered from the drawba...
the ever severe dynamic competitive environment has led to increasing complexity of strategic decision making in giant organizations. strategy formulation is one of basic processes in achieving long range goals. since, in ordinary methods considering all factors and their significance in accomplishing individual goals are almost impossible. here, a new approach based on clustering method is pro...
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