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[PDF] Top 20 Clustering K-Means Optimization with Multi- Objective Genetic Algorithm

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Clustering K-Means Optimization with Multi- Objective Genetic Algorithm

Clustering K-Means Optimization with Multi- Objective Genetic Algorithm

... the K- Means clustering is the genetic ...of genetic algorithm in optimization of K-Means clustering, among others, is in the search for images based ... See full document

6

Improvement in performance of k-means clustering algorithm using genetic algorithm based centroid selection

Improvement in performance of k-means clustering algorithm using genetic algorithm based centroid selection

... classical clustering approach namely k-means clustering ...The k-means clustering technique is improved for two major motives first the improvement of their accuracy and ... See full document

6

AHP COA Combined Algorithm for Selecting a Digital Production
Machine Design

AHP COA Combined Algorithm for Selecting a Digital Production Machine Design

... for multi-objective optimization problems: such as Ant Colony algorithm, COA (Cuckoo Algorithm, Genetic algorithm, particle swarm optimization algorithm, ... See full document

5

Determining a Cluster Centroid of K-Means Clustering Using Genetic Algorithm

Determining a Cluster Centroid of K-Means Clustering Using Genetic Algorithm

... Because the number of clusters we have as many as three, then we are also use 3 cluster. We can use Genetic Algorithm in Determining the initial value of cluster centroid. Research on Iris Data Set using a ... See full document

5

A Comparative Study on K-Means And Genetic Algorithm For Data Clustering

A Comparative Study on K-Means And Genetic Algorithm For Data Clustering

... study K-means & GA techniques are used to find out the support, confidence, memory space and time in seconds of Mushroom, Soyabean and Fishers Iris ...to K-Means algorithm.. ... See full document

9

A Multi Agent Bio  Inspired System to Map Learners with Learning Resources using Clustering Based Personalization

A Multi Agent Bio Inspired System to Map Learners with Learning Resources using Clustering Based Personalization

... engine. Clustering is defined as a technique found in data mining for identifying interesting patterns in the ...the K-Means ...the K-means clustering ...the multi-agent ... See full document

9

Multi-objective Optimization of Cloud Manufacturing Service Composition with Cloud-Entropy Enhanced Genetic Algorithm

Multi-objective Optimization of Cloud Manufacturing Service Composition with Cloud-Entropy Enhanced Genetic Algorithm

... composition into three stages: the matching of adjacent nodes, the cleaning of broken branch nodes and the combination of atomic services, and put forward three steps service composition algorithm of the ... See full document

14

Optimization of a multi-objective-multi period traveling salesman problem with pickup and delivery using genetic algorithm

Optimization of a multi-objective-multi period traveling salesman problem with pickup and delivery using genetic algorithm

... CPP objective is to determine a shortest closed route which goes across every edge at least once and delivers mail on every designated street block (Kramberger & Zerovnik, ... See full document

30

Clustering for binary data sets by using genetic algorithm incremental K means

Clustering for binary data sets by using genetic algorithm incremental K means

... Another promising algorithm to handle a large data set is Genetic Algorithms (GA). This technique was proposed by John Holland and his colleagues in the early of 1970’s. GA was inspired by the process of ... See full document

6

Bisecting K-means Algorithm Based on K-valued Selfdetermining and Clustering Center Optimization

Bisecting K-means Algorithm Based on K-valued Selfdetermining and Clustering Center Optimization

... The K-means algorithm is a typical objective function clustering method based on the prototype, the optimization of the objective function is a distance between data ... See full document

8

Parallel Processing Of Data Mining Functions Using Clustering, Optimization And Classification Techniques

Parallel Processing Of Data Mining Functions Using Clustering, Optimization And Classification Techniques

... parallel K-Medoids clustering algorithm and it was based on MapReduce paradigm to perform clustering on large-scale of ...free algorithm for determining the interesting patterns in very ... See full document

11

Medical Image Segmentation using Modified K Means Clustering

Medical Image Segmentation using Modified K Means Clustering

... of clustering which allows one piece of data to belong to two or more ...following objective function. The FCM algorithm is one of the most widely used fuzzy clustering ...FCM algorithm ... See full document

5

Hybrid optimization for k-means clustering learning enhancement

Hybrid optimization for k-means clustering learning enhancement

... to clustering (Krovi, 1992; Sheikh et ...Fast Genetic K-means Algorithm (FGKA) (Lu et ...when K-means algorithm are converted to a local optimum, both GKA and FGKA ... See full document

47

A Survey on Image Clustering using Soft Computing Techniques

A Survey on Image Clustering using Soft Computing Techniques

... this algorithm. In [21] “Diverse Fuzzy C-means” is used for clustering the ...This algorithm introducing novel diversity regularization into the traditional fuzzy c-means ...Search ... See full document

6

Enhanced K-Means Clustering Algorithm Using Collaborative Filtering Approach

Enhanced K-Means Clustering Algorithm Using Collaborative Filtering Approach

... first means used as input and in this case output is final ...last means are the means of clusters, if an algorithm is required to create a cluster then K-means will be the ... See full document

6

Research on multi-objective emergency logistics vehicle routing problem under constraint conditions

Research on multi-objective emergency logistics vehicle routing problem under constraint conditions

... Coding: In the article, a chromosome represents a feasible solution of the vehicle routing problem in the context of emergency. Each chromosome consists of two sub-strings. The first sub-string has M genes (M is the ... See full document

9

Survey on Cloud Storage Based Clustering Technique

Survey on Cloud Storage Based Clustering Technique

... The k-means algorithm is an iterative procedure for clustering which require an initial classification of ...this algorithm is based on an approach where a random set of cluster base is ... See full document

9

An Efficient Intelligent Clustering Tool based on Hybrid Fuzzified Algorithm for Electrical Data

An Efficient Intelligent Clustering Tool based on Hybrid Fuzzified Algorithm for Electrical Data

... The proposed algorithm is tested on two different data sets of IEEE 300 bus and IEEE 118 electrical bus data system. The IEEE 118 bus line diagram is shown in figure 3 and the sample data set are given in table 2. ... See full document

7

Pareto Optimal Multi-Objective Dynamical Balancing of a Slider-Crank Mechanism Using Differential Evolution Algorithm

Pareto Optimal Multi-Objective Dynamical Balancing of a Slider-Crank Mechanism Using Differential Evolution Algorithm

... of objective functions of non-superior points were mapped in a range of 0 to ...all objective-functions, the optimal point, which is called D, has the least summation of mapped objective ...four ... See full document

12

Online Full Text

Online Full Text

... the optimization process is accomplished ...that optimization without considering uncertainty generally leads to non-optimal and potentially high risk solution ...design optimization (RDO) and ... See full document

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