1. Research on Algorithm Optimization of Hidden Units Data Centre of RBF Neural Network
- Author
-
Xiao Niu Li, Jing Ying Zhao, and Hai Guo
- Subjects
Mathematical optimization ,Meta-optimization ,ComputingMethodologies_MISCELLANEOUS ,General Engineering ,k-means clustering ,Canopy clustering algorithm ,Particle swarm optimization ,Multi-swarm optimization ,Hybrid algorithm ,Metaheuristic ,FSA-Red Algorithm ,Mathematics - Abstract
Common algorithms of selecting hidden unit data center in RBF neural networks were first discussed in this essay, i.e. k-means algorithm, subtractive clustering algorithm and orthogonal least squares. Meanwhile, a hybrid algorithm mixed of k-means algorithm and particle swarm optimization algorithm was put forward. The algorithm used the position of the particles in particle swarm optimization algorithm to help deal with the defects of local clusters resulted from k-means algorithm and to make optimization with the optimal fitness of k-means particle swarm with the aim to make the final optimal fitness better satisfy the requirements.
- Published
- 2013