입자군집최적화 알고리즘을 이용한 다층퍼셉트론의 파라미터 학습 성능 개선 가능성에 관한 연구
A study on the possibility of improving the parameter learning performance of the multilayer perceptron using the particle swarm optimization algorithm
원문정보
초록
- In this paper, a study was conducted on the methodology for learning the parameters of a neural network using an evolutionary algorithm such as a particle swarm optimization algorithm. The possibility of using the particle swarm optimization algorithm for deep learning was analyzed, and various methods were considered for practical use.
목차
Abstract
Introduction
Particle Swarm Optimization
Alternative Parameter Training of Deep Learning Architecture using Particle Swarm Optimization
Acknowledgments
Conclusion
References
저자
간행물 정보
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- 간행물
- 한국경영정보학회 정기 학술대회 [KMIS Conference]
- 간기
- 반년간
- 수록기간
- 1990~2025
- 십진분류
- KDC 325 DDC 658