Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing.

Pengelompokan adalah suatu teknik pelombongan data. Di dalam bidang set data tanpa selia, tugas mengelompok ialah dengan mengumpul set data kepada kelompok yang bermakna. Pengelompokan digunakan sebagai teknik penyelesaian di dalam pelbagai bidang dengan membahagikan dan mengstruktur semula data yan...

Full description

Saved in:
Bibliographic Details
Main Author: Abubaker, Ahmad Asad
Format: Thesis
Language:en
Published: 2016
Subjects:
Online Access:http://eprints.usm.my/38568/1/Automatic_multi-objective_clustering_algorithm_using_hybrid_particle_swarm_optimization_with_simulated_annealing_by_Ahmad_Asad_Abubaker..pdf
http://eprints.usm.my/38568/
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1834501536975159296
author Abubaker, Ahmad Asad
author_facet Abubaker, Ahmad Asad
author_sort Abubaker, Ahmad Asad
building Hamzah Sendut Library
collection Institutional Repository
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
continent Asia
country Malaysia
description Pengelompokan adalah suatu teknik pelombongan data. Di dalam bidang set data tanpa selia, tugas mengelompok ialah dengan mengumpul set data kepada kelompok yang bermakna. Pengelompokan digunakan sebagai teknik penyelesaian di dalam pelbagai bidang dengan membahagikan dan mengstruktur semula data yang besar dan kompleks supaya menjadi lebih bererti justru mengubahnya kepada maklumat yang berguna. Clustering is a data mining technique. In the field of unsupervised datasets, the task of clustering is by grouping the dataset into meaningful clusters. Clustering is used as a data solution technique in various fields to divide and restructure the large and complex data to become more significant thus transform them into useful information.
format Thesis
id my.usm.eprints.38568
institution Universiti Sains Malaysia
language en
publishDate 2016
record_format eprints
spelling my.usm.eprints.38568 http://eprints.usm.my/38568/ Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing. Abubaker, Ahmad Asad QA1 Mathematics (General) Pengelompokan adalah suatu teknik pelombongan data. Di dalam bidang set data tanpa selia, tugas mengelompok ialah dengan mengumpul set data kepada kelompok yang bermakna. Pengelompokan digunakan sebagai teknik penyelesaian di dalam pelbagai bidang dengan membahagikan dan mengstruktur semula data yang besar dan kompleks supaya menjadi lebih bererti justru mengubahnya kepada maklumat yang berguna. Clustering is a data mining technique. In the field of unsupervised datasets, the task of clustering is by grouping the dataset into meaningful clusters. Clustering is used as a data solution technique in various fields to divide and restructure the large and complex data to become more significant thus transform them into useful information. 2016-12 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/38568/1/Automatic_multi-objective_clustering_algorithm_using_hybrid_particle_swarm_optimization_with_simulated_annealing_by_Ahmad_Asad_Abubaker..pdf Abubaker, Ahmad Asad (2016) Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing. PhD thesis, Universiti Sains Malaysia.
spellingShingle QA1 Mathematics (General)
Abubaker, Ahmad Asad
Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing.
title Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing.
title_full Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing.
title_fullStr Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing.
title_full_unstemmed Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing.
title_short Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing.
title_sort automatic multi-objective clustering algorithm using hybrid particle swarm optimization with simulated annealing.
topic QA1 Mathematics (General)
url http://eprints.usm.my/38568/1/Automatic_multi-objective_clustering_algorithm_using_hybrid_particle_swarm_optimization_with_simulated_annealing_by_Ahmad_Asad_Abubaker..pdf
http://eprints.usm.my/38568/
url_provider http://eprints.usm.my/