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In recent years, various artificial intelligence algorithms based on big data have gradually emerged and have been applied in short-term time series wave forecasting. Based on the measured time series data of hourly waves in Hainan offshore from 2015 to 2019, a prediction model for long-term time series waves of Hainan offshore based on Prophet algorithm is established in this paper. The daily, monthly and annual variation characteristics of waves in Hainan offshore from 2015 to 2019 are analyzed, and the waves in Hainan offshore in 2020 are predicted. The results show that the predicted values of wave height and period by prophet algorithm model are in good agreement with the measured values. Prophet algorithm model can be effectively used for long-term wave characteristic analysis and time series prediction.
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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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