摘要
Compared with the traditional time series prediction model, neural network has obvious advantages for the analysis of nonlinear time series data. However, the topology structure and the training algorithm of neural network have a great influence on the prediction accuracy. Taking stock data as an instance, this paper analyzes the impacts factors of prediction ability of neural network such as topology structure, training algorithm and dataset. The experimental results show that the training algorithm and the size of dataset have significant influence on the performance of neural network.
源语言 | 英语 |
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主期刊名 | Cyber Security Intelligence and Analytics |
编辑 | Zheng Xu, Kim-Kwang Raymond Choo, Ali Dehghantanha, Mohammad Hammoudeh, Reza Parizi |
出版商 | Springer Verlag |
页 | 1007-1014 |
页数 | 8 |
ISBN(印刷版) | 9783030152345 |
DOI | |
出版状态 | 已出版 - 2020 |
已对外发布 | 是 |
活动 | International Conference on Cyber Security Intelligence and Analytics, CSIA 2019 - Shenyang, 中国 期限: 21 2月 2019 → 22 2月 2019 |
出版系列
姓名 | Advances in Intelligent Systems and Computing |
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卷 | 928 |
ISSN(印刷版) | 2194-5357 |
ISSN(电子版) | 2194-5365 |
会议
会议 | International Conference on Cyber Security Intelligence and Analytics, CSIA 2019 |
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国家/地区 | 中国 |
市 | Shenyang |
时期 | 21/02/19 → 22/02/19 |
指纹
探究 'The Impact Factors of Neural Network Based Time Series Prediction: Taking Stock Price as an Example' 的科研主题。它们共同构成独一无二的指纹。引用此
Hou, Y., Liu, H., Xie, B., & Ding, F. (2020). The Impact Factors of Neural Network Based Time Series Prediction: Taking Stock Price as an Example. 在 Z. Xu, K.-K. R. Choo, A. Dehghantanha, M. Hammoudeh, & R. Parizi (编辑), Cyber Security Intelligence and Analytics (页码 1007-1014). (Advances in Intelligent Systems and Computing; 卷 928). Springer Verlag. https://doi.org/10.1007/978-3-030-15235-2_134