WBBA-KM: A Hybrid Weight-Based Bat Algorithm with K-Means Algorithm For Cluster Analysis

نویسندگان

چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Hybrid K-means Algorithm and Genetic Algorithm for Cluster Analysis

Cluster analysis is a fundamental technique for various filed such as pattern recognition, machine learning and so forth. However, the cluster number is predefined by users in K-means algorithm, which is unpractical to implement. Since the number of clusters is a NP-complete problem, Genetic Algorithm is employed to solve it. In addition, due to the large time consuming in conventional method, ...

متن کامل

Persistent K-Means: Stable Data Clustering Algorithm Based on K-Means Algorithm

Identifying clusters or clustering is an important aspect of data analysis. It is the task of grouping a set of objects in such a way those objects in the same group/cluster are more similar in some sense or another. It is a main task of exploratory data mining, and a common technique for statistical data analysis This paper proposed an improved version of K-Means algorithm, namely Persistent K...

متن کامل

A Hybrid Data Clustering Algorithm Using Modified Krill Herd Algorithm and K-MEANS

Data clustering is the process of partitioning a set of data objects into meaning clusters or groups. Due to the vast usage of clustering algorithms in many fields, a lot of research is still going on to find the best and efficient clustering algorithm. K-means is simple and easy to implement, but it suffers from initialization of cluster center and hence trapped in local optimum. In this paper...

متن کامل

Distance Based Hybrid Approach for Cluster Analysis Using Variants of K-means and Evolutionary Algorithm

Clustering is a process of grouping same objects into a specified number of clusters. K-means and Kmedoids algorithms are the most popular partitional clustering techniques for large data sets. However, they are sensitive to random selection of initial centroids and are fall into local optimal solution. K-means++ algorithm has good convergence rate than other algorithms. Distance metric is used...

متن کامل

Document Clustering Analysis Based on Hybrid PSO+K-means Algorithm

There is a tremendous proliferation in the amount of information available on the largest shared information source, the World Wide Web. Fast and high-quality document clustering algorithms play an important role in helping users to effectively navigate, summarize and organize the information. Recent studies have shown that partitional clustering algorithms are more suitable for clustering larg...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of Polytechnic

سال: 2020

ISSN: 1302-0900

DOI: 10.2339/politeknik.689384