Time series generation model based on multi-discriminator generative adversarial network
Aiming at the problems of expensive collection cost and missing data due to the privacy and continuity of time series data set, a multi-discriminator generative adversarial network model based on recurrent neural network was proposed, which could synthesize time series dataset that were approximatel...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2022-10-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022205/ |
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| _version_ | 1841539994859077632 |
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| author | Yanhui LU Han LIU Hang LI Guangxu ZHU |
| author_facet | Yanhui LU Han LIU Hang LI Guangxu ZHU |
| author_sort | Yanhui LU |
| collection | DOAJ |
| description | Aiming at the problems of expensive collection cost and missing data due to the privacy and continuity of time series data set, a multi-discriminator generative adversarial network model based on recurrent neural network was proposed, which could synthesize time series dataset that were approximately distributed with real data of a small scale dataset.Multi-discriminator included four discriminators in time domain, frequency domain, time-frequency domain and autocorrelation.Different discriminators could effectively recognize the features of the time series in different domains.In the experiment, the convergence of loss function, principal component analysis and error analysis were performed to evaluate the performance of the model from qualitative and quantitative perspectives.The experimental results show that the proposed model has better performance than other reference models. |
| format | Article |
| id | doaj-art-cb9e4f33f4c24f78bab0cc37bcd4a8ba |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2022-10-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-cb9e4f33f4c24f78bab0cc37bcd4a8ba2025-01-14T06:30:06ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2022-10-014316717659396326Time series generation model based on multi-discriminator generative adversarial networkYanhui LUHan LIUHang LIGuangxu ZHUAiming at the problems of expensive collection cost and missing data due to the privacy and continuity of time series data set, a multi-discriminator generative adversarial network model based on recurrent neural network was proposed, which could synthesize time series dataset that were approximately distributed with real data of a small scale dataset.Multi-discriminator included four discriminators in time domain, frequency domain, time-frequency domain and autocorrelation.Different discriminators could effectively recognize the features of the time series in different domains.In the experiment, the convergence of loss function, principal component analysis and error analysis were performed to evaluate the performance of the model from qualitative and quantitative perspectives.The experimental results show that the proposed model has better performance than other reference models.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022205/generative adversarial networktime seriesFourier transformautocorrelation functionmachine learning |
| spellingShingle | Yanhui LU Han LIU Hang LI Guangxu ZHU Time series generation model based on multi-discriminator generative adversarial network Tongxin xuebao generative adversarial network time series Fourier transform autocorrelation function machine learning |
| title | Time series generation model based on multi-discriminator generative adversarial network |
| title_full | Time series generation model based on multi-discriminator generative adversarial network |
| title_fullStr | Time series generation model based on multi-discriminator generative adversarial network |
| title_full_unstemmed | Time series generation model based on multi-discriminator generative adversarial network |
| title_short | Time series generation model based on multi-discriminator generative adversarial network |
| title_sort | time series generation model based on multi discriminator generative adversarial network |
| topic | generative adversarial network time series Fourier transform autocorrelation function machine learning |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022205/ |
| work_keys_str_mv | AT yanhuilu timeseriesgenerationmodelbasedonmultidiscriminatorgenerativeadversarialnetwork AT hanliu timeseriesgenerationmodelbasedonmultidiscriminatorgenerativeadversarialnetwork AT hangli timeseriesgenerationmodelbasedonmultidiscriminatorgenerativeadversarialnetwork AT guangxuzhu timeseriesgenerationmodelbasedonmultidiscriminatorgenerativeadversarialnetwork |