clustering problem
Rapid Ant based clustering-genetic algorithm (RAC-GA) with local search for clustering problem Pages 435-444 Download PDF
... Here we have proposed a novel combinational approach to improve the ACO algorithm for clustering problem. RAC-GA uses the advantages of RAC to be rapid enough to find proper solutions and it utilizes the ...
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Randomized heuristics for the Capacitated Clustering Problem
... Capacitated Clustering Problem (CCP) is to find a partition of the set of points into different groups in order to maximize some weighted measure of the distance among the points in the same ...on ...
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Converting Ensemble Clustering Problem to a Mathematical Optimization Problem and Providing an Approach to Solve Based on Optimization Toolbox
... in clustering. Various criteria have been set for considering the clustering and evaluating its performance and many researchers through different ways have assessed them by using these ...
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Clustering with Bregman Divergences
... the clustering problem is ...hard clustering (Dhillon et al., 2003) approach solved the problem of dis- tributional clustering with a formulation involving loss in Shannon’s mutual ...
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Preliminary Review of Swarm Intelligence: A Clever Algorithm and Data Clustering
... systems. Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups ...The clustering problem has been addressed in many contexts and by ...
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Non-Redundant Overlapping Clustering: Algorithms and Applications
... lower and upper bound that dimension. On other non-relevant dimensions, the cell intervals are the full domains. The algorithms in this scheme can generate all possible clusters or only high-quality ones, the quality ...
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Clustering Algorithm As A Planning Support Tool For Rural Electrification Optimization
... study clustering algorithm was developed to optimize electrification plans by screening and grouping potential customers to be supplied with ...in clustering problem which combines conceptual and ...
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Application of Capital Asset Pricing Model in Indian Stock Market
... sparsity problem in movie recommendation system that has the ability to recommend movies to a new user as well as the ...Rater problem , Unusual user problem. K- mean clustering is the most ...
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Heterogeneous information network based clustering for precision traditional Chinese medicine
... case, clustering on heterogeneous information networks has richer seman- tics, but it also faces more ...the clustering problem in Attributed ...the clustering performance, but they were con- ...
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Title: Control Channel Allocation in Cognitive Radio Networks using Clustering
... The clustering problem is formulated as a bipartite graph problem given the inherent partioning of the network into clusters due to the space- and time-dependent spectrum ...The clustering is ...
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More work on K Means Clustering Algorithm: The Dimensionality Problem
... The K-means algorithm is found to be the best applied to numeric data [14], and the modifications, discussed above, dealing with numerical data set are very encouraging. However, the application of the K-means algorithm ...
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Online Full Text
... this problem by optimizing the nodes' power ...is clustering, but optimum clustering of wireless sensor network is an NP-Hard ...this clustering problem by finding the number of ...
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Mining Text Document on the Utilization of Side Information
... the clustering problem, we tend to note that such an approach willalso be extended in essence to alternative data mining issues during which auxiliary information is available with ...classification ...
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A Minimum Cost Effective Cluster Algorithm Using UWSN
... dependable clustering problem, which is to construct a cluster hierarchy with each cluster member covered by two different cluster ...This problem is similar to the domatic partition problem ...
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Reflective dialogues and students’ problem solving ability analysis using clustering
... and problem solving considerably improved as compared to the previous experiment; yet, it was still far from ...students’ problem solving skills but the results did not show that significant impact of ...
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A New Approach to Generate Rules in Genetic Algorithm Solution to a Job Shop Schedule by Fuzzy Clustering
... shop problem which has an optimal solution generated by a ...6 problem instance, first proposed by Muth and Thompson [10] has been selected as the benchmark ...This problem has six jobs, each with ...
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Capacitated Clustering and Collection of Solid Waste in Kwadaso Estate, Kumasi
... This problem is even more crucial for large cities in developing countries due to the hot ...Routing Problem (CARP) in Kwadaso, a suburb of Kumasi, ...
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Edge Enhanced Fuzzy C Means Algorithm for Hippocampus Segmentation and Abnormality Identification
... The presence of many non-brain tissues will in general affect the clinical diagnosis and treatment planning while performing MR image analysis. Thus it always becomes mandatory to preprocess human brain to delineate ...
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File Clustering using Forensic Analysis System
... accomplish. Clustering is the unverified organization of designs that is data items, remarks, or feature vectors into groups ...text clustering algorithms to forensic examination of computers seized in ...
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A REVIEW ON FORENSIC DOCUMENT ANALYSIS USUNG APRIORIALGORITHM
... In existing system applied the k-means method to categorical objects, two main problems are encountered, namely, the formation of cluster centers and the calculation of dissimilarity between objects and cluster centers. ...
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