skip to content
A comparison of particle swarm optimization algorithms in data clustering Preview this item
ClosePreview this item
Checking...

A comparison of particle swarm optimization algorithms in data clustering

Author: Yu-Kuang Chung
Publisher: [Long Beach, California] : California State University, Long Beach, 2010.
Dissertation: M.S. California State University, Long Beach 2010
Series: California State University, Long Beach.; Master's thesis collection, Dept. of Computer Engineering and Computer Science.
Edition/Format:   Thesis/dissertation : Thesis/dissertation   Computer File : English
Summary:
Abstract: This thesis is an investigation into the use of Particle Swarm Optimization (PSO) techniques in data clustering. The PSO is an optimization technique based on swarm intelligence. The technique has been extended to data clustering. Several algorithms have been developed with some degree of success. In particular, three algorithms have been proposed. These include Dynamic Clustering using Particle Swarm  Read more...
Rating:

(not yet rated) 0 with reviews - Be the first.

Subjects
More like this

Find a copy online

Links to this item

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Genre/Form: Academic theses
Material Type: Thesis/dissertation, Internet resource
Document Type: Book, Computer File, Internet Resource
All Authors / Contributors: Yu-Kuang Chung
ISBN: 9781124247687 1124247688
OCLC Number: 1028677002
Description: vii, 60 leaves : illustrations, charts
Series Title: California State University, Long Beach.; Master's thesis collection, Dept. of Computer Engineering and Computer Science.
Responsibility: by Yu-Kuang Chung.

Abstract:

Abstract: This thesis is an investigation into the use of Particle Swarm Optimization (PSO) techniques in data clustering. The PSO is an optimization technique based on swarm intelligence. The technique has been extended to data clustering. Several algorithms have been developed with some degree of success. In particular, three algorithms have been proposed. These include Dynamic Clustering using Particle Swarm Optimization (DCPSO), Exponential Particle Swarm Optimization (EPSO), and Particle Swarm-Like Agents Approach for Dynamically Adaptive Data Clustering (PSDC). This thesis attempts to compare these algorithms in the context of data clustering in terms of efficiency, convergence, and complexity. The comparison shows that each algorithm performs differently according to the size and dimensions of the datasets.

Reviews

User-contributed reviews
Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Tags

Be the first.
Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Linked Data


Primary Entity

<http://www.worldcat.org/oclc/1028677002> # A comparison of particle swarm optimization algorithms in data clustering
    a schema:CreativeWork, bgn:Thesis, schema:Book ;
    bgn:inSupportOf "" ;
    library:oclcnum "1028677002" ;
    library:placeOfPublication <http://id.loc.gov/vocabulary/countries/cau> ;
    library:placeOfPublication <http://experiment.worldcat.org/entity/work/data/4818813254#Place/long_beach_california> ; # Long Beach, California
    schema:about <http://experiment.worldcat.org/entity/work/data/4818813254#Topic/swarm_intelligence_mathematical_models> ; # Swarm intelligence--Mathematical models
    schema:about <http://experiment.worldcat.org/entity/work/data/4818813254#Topic/cluster_analysis> ; # Cluster analysis
    schema:creator <http://experiment.worldcat.org/entity/work/data/4818813254#Person/chung_yu_kuang> ; # Yu-Kuang Chung
    schema:datePublished "2010" ;
    schema:description "Abstract: This thesis is an investigation into the use of Particle Swarm Optimization (PSO) techniques in data clustering. The PSO is an optimization technique based on swarm intelligence. The technique has been extended to data clustering. Several algorithms have been developed with some degree of success. In particular, three algorithms have been proposed. These include Dynamic Clustering using Particle Swarm Optimization (DCPSO), Exponential Particle Swarm Optimization (EPSO), and Particle Swarm-Like Agents Approach for Dynamically Adaptive Data Clustering (PSDC). This thesis attempts to compare these algorithms in the context of data clustering in terms of efficiency, convergence, and complexity. The comparison shows that each algorithm performs differently according to the size and dimensions of the datasets."@en ;
    schema:exampleOfWork <http://worldcat.org/entity/work/id/4818813254> ;
    schema:genre "Academic theses"@en ;
    schema:inLanguage "en" ;
    schema:isPartOf <http://experiment.worldcat.org/entity/work/data/4818813254#Series/master_s_thesis_collection_dept_of_computer_engineering_and_computer_science> ; # Master's thesis collection, Dept. of Computer Engineering and Computer Science.
    schema:name "A comparison of particle swarm optimization algorithms in data clustering"@en ;
    schema:productID "1028677002" ;
    schema:publication <http://www.worldcat.org/title/-/oclc/1028677002#PublicationEvent/long_beach_california_california_state_university_long_beach_2010> ;
    schema:publisher <http://experiment.worldcat.org/entity/work/data/4818813254#Agent/california_state_university_long_beach> ; # California State University, Long Beach
    schema:url <http://proquest.umi.com/pqdweb?did=2157389621&sid=1&Fmt=2&clientId=14436&RQT=309&VName=PQD> ;
    schema:workExample <http://worldcat.org/isbn/9781124247687> ;
    wdrs:describedby <http://www.worldcat.org/title/-/oclc/1028677002> ;
    .


Related Entities

<http://experiment.worldcat.org/entity/work/data/4818813254#Agent/california_state_university_long_beach> # California State University, Long Beach
    a bgn:Agent ;
    schema:name "California State University, Long Beach" ;
    .

<http://experiment.worldcat.org/entity/work/data/4818813254#Organization/california_state_university_long_beach> # California State University, Long Beach.
    a schema:Organization ;
    schema:name "California State University, Long Beach." ;
    .

<http://experiment.worldcat.org/entity/work/data/4818813254#Person/chung_yu_kuang> # Yu-Kuang Chung
    a schema:Person ;
    schema:familyName "Chung" ;
    schema:givenName "Yu-Kuang" ;
    schema:name "Yu-Kuang Chung" ;
    .

<http://experiment.worldcat.org/entity/work/data/4818813254#Place/long_beach_california> # Long Beach, California
    a schema:Place ;
    schema:name "Long Beach, California" ;
    .

<http://experiment.worldcat.org/entity/work/data/4818813254#Series/master_s_thesis_collection_dept_of_computer_engineering_and_computer_science> # Master's thesis collection, Dept. of Computer Engineering and Computer Science.
    a bgn:PublicationSeries ;
    schema:creator <http://experiment.worldcat.org/entity/work/data/4818813254#Organization/california_state_university_long_beach> ; # California State University, Long Beach.
    schema:hasPart <http://www.worldcat.org/oclc/1028677002> ; # A comparison of particle swarm optimization algorithms in data clustering
    schema:name "Master's thesis collection, Dept. of Computer Engineering and Computer Science." ;
    schema:name "[Master's thesis collection, Dept. of Computer Engineering and Computer Science]" ;
    .

<http://experiment.worldcat.org/entity/work/data/4818813254#Topic/swarm_intelligence_mathematical_models> # Swarm intelligence--Mathematical models
    a schema:Intangible ;
    schema:name "Swarm intelligence--Mathematical models"@en ;
    .

<http://worldcat.org/isbn/9781124247687>
    a schema:ProductModel ;
    schema:isbn "1124247688" ;
    schema:isbn "9781124247687" ;
    .


Content-negotiable representations

Close Window

Please sign in to WorldCat 

Don't have an account? You can easily create a free account.