Using genetic algorithms in K-means fast learning artificial neural networks for clustering
This research project studies the KFLANN in depth and introduces Genetic Algorithms (GAs) as a possible solution for searching through the parameter space to effectively and efficiently extract suitable values to d and ?. It is also able to determine significant features of the data that help achiev...
Saved in:
Main Author: | Yin, Xiang |
---|---|
Other Authors: | Tay Leng Phuan |
Format: | Theses and Dissertations |
Published: |
2008
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/2560 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Similar Items
-
Hierarchical clustering using K-Iterations Fast Learning Artificial Neural Networks (KFLANN)
by: Wong, Lai Ping
Published: (2008) -
Towards general semi-supervised clustering using a cognitive reinforcement K-Iteration fast learning artificial neural network (R-Kflann)
by: Tse, Rina
Published: (2010) -
Gains self-tuning of a large compliance system by combining artificial neural networks and genetic algorithms
by: Yuan, Yuan.
Published: (2009) -
Complex-valued neural networks and their learning algorithms
by: Savitha Ramasamy.
Published: (2011) -
Hybrid deep neural network and deep reinforcement learning for algorithmic finance
by: Ooi, Min Hui
Published: (2022)