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...
Saved in:
主要作者: | Mohd. Zin, Zalhan |
---|---|
格式: | Thesis |
語言: | English |
出版: |
2016
|
主題: | |
在線閱讀: | 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 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
相似書籍
-
Dimension reduction and clustering of high dimensional data using auto associative neural networks
由: Mohd. Zin, Zalhan, et al.
出版: (2013) -
Dimension reduction and clustering of high dimensional data using auto-associative neural networks
由: Mohd. Zin, Zalhan, et al.
出版: (2013) -
A Novel Self-Organizing Mapping Model for Multidimensional Data Visualization, Classification, and Clustering
由: Yii, Ming Leong
出版: (2017) -
Cluster identification and separation in the growing self-organizing map: Application in protein sequence classification
由: Ahmad, N.
出版: (2010) -
Hybrid self organizing map for overlapping clusters
由: Md. Sap, Mohd. Noor, et al.
出版: (2008)