[PDF] Top 20 A Novel Approach Towards K-Mean Clustering Algorithm With PSO
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A Novel Approach Towards K-Mean Clustering Algorithm With PSO
... data clustering approach (PSO and K-Means) has been ...proposed approach with both individual algorithms has been done using on Matlab Version ...proposed approach have better ... See full document
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A NOVEL APPROACH OF FEATURE REDUCTION USING PSO AND GENETIC ALGORITHM
... PCA is partial to re-expressing the data as amalgamation of its basis vectors. A main disadvantage of PCA is that each PC is a linear grouping of all the original variables, therefore leading to a potentially tricky ... See full document
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Parallel Implementation of Fuzzy Clustering Algorithm Based on MapReduce Computing Model of Hadoop –A Detailed Survey
... data clustering involving large ...an approach to Fuzzy clustering which runs on ...Fuzzy K-mean clustering in MapReduce on ... See full document
5
A Novel Clustering Algorithm Using K means (CUK)
... proposed algorithm we try to reach the global optimal as possible as we can through multiple splitting using K-means and merging with respect to average mean ...runs K-means with one ... See full document
6
An Effective Clustering Algorithm for Transaction Databases Based on K-Mean
... Unlike text and webpages, the value of attributes in transaction databases is Boolean, such as in transaction records of supermarkets or banks. The traditional clustering approach may lose its effectiveness ... See full document
5
A Novel Design Specification Distance (DSD) based K Mean Clustering Performance Evaluation on Engineering Materials' Database
... Advancement in sensing and digital storage technologies and their dramatic growth in the applications ranging from market analysis to scientific data explorations have created many high-volume and high dimensional data ... See full document
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Clustering based information retrieval with the aco and the k-means clustering algorithm
... the clustering of the documents. The proposed approach performs the information retrieval through pre-processing, feature selection, and ...ACO algorithm for the feature selection and the ... See full document
6
Hybrid K Mean Clustering Algorithm for Crop Production Analysis in Agriculture
... information. Clustering algorithms are extensively used in the field of precision agriculture for different ...using clustering supports variable rate fertilizer ...Fuzzy clustering technique is used ... See full document
5
Detect Frauds in Credit Card using Data Mining Techniques
... Model, K-mean clustering algorithm, K- nearest neighbor, Decision Tree, Fusion approach due using dumpster Shafer, Bayesian Network, Neural Network, SVM and Logistic Regression ... See full document
5
Application of Particle Swarm Optimization in Data Clustering: A Survey
... the K-means is not convex[10] and hence it may contain local ...the K-means algorithm depends on the initial choice of the cluster ...that K-means algorithm should be affected by noise ... See full document
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K Mean and Fuzzy Clustering Algorithm Predicated Brain Tumor Segmentation And Area Estimation
... an approach to giving so as to handle the information the fractional participation worth to every pixel in the ...C-Means algorithm has several advantages like ... See full document
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OPTIMIZATION OF HIGH VOLTAGE POWER SUPPLY FOR INDUSTRIAL MICROWAVE GENERATORS FOR ONE MAGNETRON
... of k-means algorithm depend on the initialization of cluster centers and the final solution converges to local ...a clustering approach that combines ideas from modified particle swarm ... See full document
7
A Review of K-mean Algorithm
... new approach of data clustering based on the improvement of sensitivity of initial center of ...This algorithm will decrease the complexity and effort of numerical calculation and maintain the ... See full document
5
Study and Implementing K mean Clustering Algorithm on English Text and Techniques to Find the Optimal Value of K
... the approach of assigning a set of items to one similar class called cluster and the process termed as ...Document clustering is one of the rapidly developing, research area for decades and considered a ... See full document
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Real World Document Clustering Using Modified Balanced Iterative Reducing and Clustering using Hierarchies
... Document clustering is used in many fields such as data mining and information ...the clustering results of K-Mean approach ,agglomerative approach , partitioned approach ... See full document
6
A Review on Various Approaches for data Preserving Clustering in Data Mining
... Using K- Mean Clustering Algorithm” Clustering is one of the very important technique used for classification of large dataset and widely applied to many applications including analysis ... See full document
5
Online Full Text
... However, PSO often leads to premature convergence, especially in complex multi-peak search problems such clustering of ...the K-means, PSO, NM-PSO, K-PSO, and ... See full document
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Integration of PSO and K-means clustering algorithm for structural-based alert correlation model
... PSO starts by initializing a population of random solutions or swarm. It then evaluates each solution (or particle) in the swarm and searches for the optima (or leader) by updating generations where they ... See full document
6
Enhanced K-Means Clustering Algorithm Using Collaborative Filtering Approach
... In clustering a set of essentials is separated into uniform ...based clustering algorithms in the area of research. But in the original K-means the quality of the resulting clusters mostly depends on ... See full document
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NORMALIZATION INDEXING BASED ENHANCED GROUPING K-MEAN ALGORITHM
... of clustering high dimensional ...of clustering approach will be suitable for all types of data, even all high dimensional ...and clustering is no ... See full document
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