A Human Community-Based Genetic Algorithm Model (HCBGA)
Sebagai satu model gelintaran, Algoritma Genetik (GA), telah membuktikan kejayaannya dalam banyak apikasi. Walau bagaimanapun, beberapa penyelidik menyatakan bahawa GA mempunyai “convergence” yang perlahan. Keperlahanan ini berpunca daripada kerawakan dalam kebanyakan operasinya. Oleh itu, ramai pen...
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my-usm-ep.415582019-04-12T05:26:59Z A Human Community-Based Genetic Algorithm Model (HCBGA) 2009-11 Al-Madi, Nagham Azmi Qasim QA75.5-76.95 Electronic computers. Computer science Sebagai satu model gelintaran, Algoritma Genetik (GA), telah membuktikan kejayaannya dalam banyak apikasi. Walau bagaimanapun, beberapa penyelidik menyatakan bahawa GA mempunyai “convergence” yang perlahan. Keperlahanan ini berpunca daripada kerawakan dalam kebanyakan operasinya. Oleh itu, ramai penyelidik terkini telah menggunakan populasi berstruktur dalam GA untuk mengurangkan kerawakan seperti model algoritma genetik pulau (IGA), model algoritma genetik bersel (CGA) dan model lain. As a general search model, Genetic Algorithm (GA) has proved its success in many applications. However, several researchers argue that GA has slow convergence. This shortfall is due to the randomness in most of its operations. Hence, recently researches have employed structured populations in GA to reduce this randomness, such as in the island genetic algorithm model (IGA), cellular genetic algorithm model (CGA) and other models. 2009-11 Thesis http://eprints.usm.my/41558/ http://eprints.usm.my/41558/1/Nagham_Azmi_Qasim_Al-Madi24.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Komputer |
| institution |
Universiti Sains Malaysia |
| collection |
USM Institutional Repository |
| language |
English |
| topic |
QA75.5-76.95 Electronic computers Computer science |
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QA75.5-76.95 Electronic computers Computer science Al-Madi, Nagham Azmi Qasim A Human Community-Based Genetic Algorithm Model (HCBGA) |
| description |
Sebagai satu model gelintaran, Algoritma Genetik (GA), telah membuktikan kejayaannya dalam banyak apikasi. Walau bagaimanapun, beberapa penyelidik menyatakan bahawa GA mempunyai “convergence” yang perlahan. Keperlahanan ini berpunca daripada kerawakan dalam kebanyakan operasinya. Oleh itu, ramai penyelidik terkini telah menggunakan populasi berstruktur dalam GA untuk mengurangkan kerawakan seperti model algoritma genetik pulau (IGA), model algoritma genetik bersel (CGA) dan model lain.
As a general search model, Genetic Algorithm (GA) has proved its success in many applications. However, several researchers argue that GA has slow convergence. This shortfall is due to the randomness in most of its operations. Hence, recently researches have employed structured populations in GA to reduce this randomness, such as in the island genetic algorithm model (IGA), cellular genetic algorithm model (CGA) and other models. |
| format |
Thesis |
| qualification_name |
Doctor of Philosophy (PhD.) |
| qualification_level |
Doctorate |
| author |
Al-Madi, Nagham Azmi Qasim |
| author_facet |
Al-Madi, Nagham Azmi Qasim |
| author_sort |
Al-Madi, Nagham Azmi Qasim |
| title |
A Human Community-Based Genetic
Algorithm Model
(HCBGA)
|
| title_short |
A Human Community-Based Genetic
Algorithm Model
(HCBGA)
|
| title_full |
A Human Community-Based Genetic
Algorithm Model
(HCBGA)
|
| title_fullStr |
A Human Community-Based Genetic
Algorithm Model
(HCBGA)
|
| title_full_unstemmed |
A Human Community-Based Genetic
Algorithm Model
(HCBGA)
|
| title_sort |
human community-based genetic
algorithm model
(hcbga) |
| granting_institution |
Universiti Sains Malaysia |
| granting_department |
Pusat Pengajian Sains Komputer |
| publishDate |
2009 |
| url |
http://eprints.usm.my/41558/1/Nagham_Azmi_Qasim_Al-Madi24.pdf |
| _version_ |
1747820931877699584 |