Multi-Column RBF Neural Network Using Adaptive and Non-Adaptive Particle Swarm Optimization
- Published
- Source
- arXiv
- Paper number
- 312
- Field
- Neural Networks
- arXiv ID
- 2606.05150
Key points
- Error correction, the state-of-the-art gradient-based learning method, chooses the optimal hidden units to improve accuracy.
- Both ErrCor and PSO demonstrate improved results and competitive convergence.
- Inspired by the success of MCRN, the authors propose two new approaches for improving PSO performance: multi-column RBFN with PSO, or MC-PSO, and multi-column RBFN with APSO, or MC-APSO.
Paper links
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