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ZHOU Xinyu, postgraduate, majors in deep learning and GPS coordinate time series, E-mail: xinyuzhouxy@163.com
Outline
This paper applies generative adversarial networks (GAN) to the denoising of GPS coordinate time series. The generator produces time series data, which is then distinguished from clean time series data by the discriminator. During training, the generator is iteratively optimized until the discriminator can no longer differentiate between the generated data and the real clean data, thereby achieving the denoising effect. Simulation results show that, compared with traditional methods such as WNNM, BiLSTM, and SSA, the GAN method achieves the closest correlation with the original noise in key indicators such as residual amplitude, residual spectral index, and velocity uncertainty, demonstrating more efficient denoising performance. Experimental results using real data further validate the effectiveness of the proposed algorithm in denoising actual GPS coordinate time series.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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