NDLI: KF-PSO: Hybridization of particle swarm optimization and kernel-based fuzzy C means algorithm

Content Provider	IEEE Xplore Digital Library
Author	Binu, D. George, A.
Copyright Year	2013
Description	Author affiliation: Aloy Labs., Bangalore, India (Binu, D.; George, A.)
Abstract	In recent times, clustering has been well known for various researchers due to various applications in most of the fields like, telecommunication, networking, biomedical domain and so on. So, various attempts have been already made by the researchers to develop a better algorithm for clustering. One of the procedures well known among the researchers is optimization that has been effectively utilized for clustering. In most of the clustering, the objective function is to minimize the intra cluster distance among the data points. Here, we have made significant trial in developing optimization based clustering algorithm utilizing kernel-based FCM and PSO algorithm. The objective function for minimization is taken from kernel-based FCM and the same objective is solved using PSO algorithm. The algorithm developed based on these scenarios are named as, KF-PSO. At first, the input data is given to PSO algorithm and the final best cluster centers are chosen from PSO algorithm useful for grouping based on the objective of the kernel clustering. Finally, the experimentation have been performed in various datasets and from the results, we have showed that the proposed hybrid algorithm achieved 98% and 90.5 % accuracy in iris and wine dataset.
Starting Page	512
Ending Page	515
File Size	143567
Page Count	4
File Format	PDF
ISBN	9781479924325
e-ISBN	9781467362177
DOI	10.1109/ICACCI.2013.6637224
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-22
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Iris Accuracy Kernel-based fuzzy c means algorithm (KFCM) Clustering algorithms Linear programming Encoding Clustering Particle swarm optimization Optimization Clustering accuracy
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Kernel based rough fuzzy c-Means clustering optimized using particle swarm optimization

Techniques for intuitionistic fuzzy kernel clustering based on particle swarm optimization

A Novel NN-Based Soft Sensor Based on Modified Fuzzy Kernel Clustering for Fermentation Process

Remote sensing image classification and recognition based on KFCM

Hybridization of particle swarm optimization with unsupervised clustering algorithms for image segmentation.

The proposal of a fuzzy clustering algorithm based on particle swarm

Unsupervised intrusion detection algorithm based on association amendment

Developing kernel intuitionistic fuzzy c-means clustering for e-learning customer analysis

Color Image Segmentation Using Kernalized Fuzzy C-means Clustering

KF-PSO: Hybridization of particle swarm optimization and kernel-based fuzzy C means algorithm

Similar Documents

Kernel based rough fuzzy c-Means clustering optimized using particle swarm optimization

Techniques for intuitionistic fuzzy kernel clustering based on particle swarm optimization

A Novel NN-Based Soft Sensor Based on Modified Fuzzy Kernel Clustering for Fermentation Process

Remote sensing image classification and recognition based on KFCM

Hybridization of particle swarm optimization with unsupervised clustering algorithms for image segmentation.

The proposal of a fuzzy clustering algorithm based on particle swarm

Unsupervised intrusion detection algorithm based on association amendment

Developing kernel intuitionistic fuzzy c-means clustering for e-learning customer analysis

Color Image Segmentation Using Kernalized Fuzzy C-means Clustering

KF-PSO: Hybridization of particle swarm optimization and kernel-based fuzzy C means algorithm