Ho-Yin Wong1, Guan-Yan Yang1,*, Kuo-Hui Yeh2, Farn Wang1
The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.1, pp. 1-4, 2024, DOI:10.32604/icces.2024.013279
Abstract 1 Introduction
This paper explores various strategies to enhance neural network performance, including adjustments to network architecture, selection of activation functions and optimizers, and regularization techniques. Hyperparameter optimization is a widely recognized approach for improving model performance [2], with methods such as grid search, genetic algorithms, and particle swarm optimization (PSO) [3] previously utilized to identify optimal solutions for neural networks. However, these techniques can be complex and challenging for beginners. Consequently, this research advocates for the use of SSO, a straightforward and effective method initially applied to the LeNet model in 2023 [4]. SSO optimizes… More >
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