Enhanced data clustering and classification using auto-associative neural networks and self organizing maps
This thesis presents a number of investigations leading to introduction of novel applications of intelligent algorithms in the fields of informatics and analytics. This research aims to develop novel methodologies to reduce dimensions and clustering of highly non-linear multidimensional data. Improv...
محفوظ في:
المؤلف الرئيسي: | Mohd. Zin, Zalhan |
---|---|
التنسيق: | أطروحة |
اللغة: | English |
منشور في: |
2016
|
الموضوعات: | |
الوصول للمادة أونلاين: | http://eprints.utm.my/id/eprint/78096/1/ZalhanMohdZinPMJIT20161.pdf http://eprints.utm.my/id/eprint/78096/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:92255 |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Dimension reduction and clustering of high dimensional data using auto associative neural networks
بواسطة: Mohd. Zin, Zalhan, وآخرون
منشور في: (2013) -
Dimension reduction and clustering of high dimensional data using auto-associative neural networks
بواسطة: Mohd. Zin, Zalhan, وآخرون
منشور في: (2013) -
A Novel Self-Organizing Mapping Model for Multidimensional Data Visualization, Classification, and Clustering
بواسطة: Yii, Ming Leong
منشور في: (2017) -
Cluster identification and separation in the growing self-organizing map: Application in protein sequence classification
بواسطة: Ahmad, N.
منشور في: (2010) -
Hybrid self organizing map for overlapping clusters
بواسطة: Md. Sap, Mohd. Noor, وآخرون
منشور في: (2008)