作者
Arie Rachmad Syulistyo, Dwi Marhaendro Jati Purnomo, Muhammad Febrian Rachmadi, Adi Wibowo
发表日期
2016/2/15
期刊
Jurnal Ilmu Komputer dan Informasi
卷号
9
期号
1
页码范围
52-58
简介
Neural network attracts plenty of researchers lately. Substantial number of renowned universities have developed neural network for various both academically and industrially applications. Neural network shows considerable performance on various purposes. Nevertheless, for complex applications, neural network’s accuracy significantly deteriorates. To tackle the aforementioned drawback, lot of researches had been undertaken on the improvement of the standard neural network. One of the most promising modifications on standard neural network for complex applications is deep learning method. In this paper, we proposed the utilization of Particle Swarm Optimization (PSO) in Convolutional Neural Networks (CNNs), which is one of the basic methods in deep learning. The use of PSO on the training process aims to optimize the results of the solution vectors on CNN in order to improve the recognition accuracy. The data used in this research is handwritten digit from MNIST. The experiments exhibited that the accuracy can be attained in 4 epoch is 95.08%. This result was better than the conventional CNN and DBN. The execution time was also almost similar to the conventional CNN. Therefore, the proposed method was a promising method.
学术搜索中的文章
AR Syulistyo, DMJ Purnomo, MF Rachmadi, A Wibowo - Jurnal Ilmu Komputer dan Informasi, 2016