Parameter optimization of evolving spiking neural network with dynamic population particle swarm optimization
Evolving Spiking Neural Network (ESNN) is widely used in classification problem. However, ESNN like any other neural networks is incapable to find its own parameter optimum values, which are crucial for classification accuracy. Thus, in this study, ESNN is integrated with an improved Particle Swarm...
Saved in:
主要作者: | Md. Said, Nur Nadiah |
---|---|
格式: | Thesis |
语言: | English |
出版: |
2018
|
主题: | |
在线阅读: | http://eprints.utm.my/id/eprint/81484/1/NurNadiahMdSaidMFC2018.pdf |
标签: |
添加标签
没有标签, 成为第一个标记此记录!
|
相似书籍
-
Parameter optimization of evolving spiking neural networks using improved firefly algorithm for classification tasks
由: Roslan, Farezdzuan
出版: (2018) -
Particle swarm optimization for neural network learning enhancement
由: Abdull Hamed, Haza Nuzly
出版: (2006) -
The impact of VMAX activation function in particle swarm optimization neural network
由: Lee, Yiew Siang
出版: (2008) -
Comparison of social network structure for particle swarm optimization
由: Chey, Kok Huat
出版: (2008) -
Hybrid particle swarm optimization-artificial neural network gender classifier for trabecular bone morphology
由: Sahadun, Nur Afiqah
出版: (2014)