| 基于支持向量机的长江口气象潮预报方法研究 |
| 作者:张策 石景元 王晶晶 |
| 单位:上海海事测绘中心, 上海 200090 |
| 关键词:长江口 支持向量机 气象潮 预报 |
| 分类号:P732 |
|
| 出版年·卷·期(页码):2025·42·第六期(1-5) |
|
摘要:
|
| 以长江口实测潮位、气象逐时资料为基础,建立了基于支持向量机的气象潮预报模型,研究探讨了长江口水域气象潮预报的可行性,认为潮流应作为支持向量机的输入因子之一;通过将支持向量机气象潮预报值与长江口部分潮位站天文潮预报值叠加,修正天文潮预报结果。经与实测资料对比发现,该方法可明显提高潮位预报精度。 |
| Based on the measured tide level and hourly meteorological data in the Yangtze River Estuary, a Support Vector Machine model for meteorological tide prediction is established, and the feasibility of meteorological tide prediction in the Yangtze River estuary is discussed. The results suggest that the tidal current could be one of the input factors of Support Vector Machine. Superposing the predicted meteorological tide on the predicted astronomical tide at some tide stations corrects the predicted astronomical tide in the Yangtze River Estuary, which improves the precision of the tide level forecasts significantly. |
|
参考文献:
|
[1] 姜兆敏,王如云,黄金城.风暴潮与天文潮非线性相互作用的理论分析[J].河海大学学报(自然科学版), 2004, 32(4):447-450.JIANG Z M, WANG R Y, HUANG J C. Nonlinear interaction between storm surges and astronomical tides[J]. Journal of Hohai University (Natural Sciences), 2004, 32(4):447-450. [2] 李煜.非负矩阵分解在潮汐分析和预报中的应用研究[D].上海:上海海洋大学, 2016.LI Y. Study on nonnegative matrix factorization on tidal analysis and prediction[D]. Shanghai:Shanghai Ocean University, 2016. [3] 张承志.伽利略卫星的平衡形状参数和潮汐耗散因子[J].天文学进展, 2001, 19(2):151-155.ZHANG C Z. Equilibrium shapes and tidal dissipation factors of Galilean satellites[J]. Progress in Astronomy, 2001, 19(2):151-155. [4] 刘潘,李树军,艾丛芳.不同潮汐预报模式在近海海域的准确度评估[J].水利规划与设计, 2017(10):73-76.LIU P, LI S J, AI C F. Accuracy evaluation of different tidal forecasting models in offshore waters[J]. Water Resources Planning and Design, 2017(10):73-76. [5] 林勋励.长江口天文潮预报修正的一种方法[J].海洋预报, 1985(1):34-42.LIN X L. An adjusting method of astronomical tide forecast in the Changjiang estuary[J]. Marine Forecasts, 1985(1):34-42. [6] 王代锋,洪华生,商少平,等.基于潮汐表数据同化的天文潮数值预报模型及其模拟预报效果[J].台湾海峡, 2010, 29(2):154-158.WANG D F, HONG H S, SHANG S P, et al. A numerical model for tide forecasting from assimilation of tide table data and its forecasting results[J]. Journal of Oceanography in Taiwan Strait,2010, 29(2):154-158. [7] 王青颜.海口湾风暴增水与天文潮非线性关系初步分析[J].海洋预报, 2005, 22(1):45-49.WANG Q Y. Preliminary analysis of the nonlinear relationship between storm surge and astronomical tide in Haikou Bay[J].Marine Forecasts, 2005, 22(1):45-49. [8] 钱睿智,李国芳,王永东.南水北调东线源头潮汐预报模型研究[J].人民长江, 2018, 49(20):35-39.QIAN R Z, LI G F, WANG Y D. Research on tidal forecasting model for source of eastern route project of south-to-north water diversion[J]. Yangtze River, 2018, 49(20):35-39. [9] 张泽国,尹建川,柳成.基于Grey-GMDH的模块化实时潮汐预报[J].中国海洋大学学报, 2018, 48(11):140-146.ZHANG Z G, YIN J C, LIU C. Modular real-time tidal level prediction based on Grey-GMDH[J]. Periodical of Ocean University of China, 2018, 48(11):140-146. [10] 柳成,尹建川.一种高精度的短期潮汐预报模型[J].上海海事大学学报, 2016, 37(3):74-80.LIU C, YIN J C. A high-accuracy short-term tide prediction model[J]. Journal of Shanghai Maritime University, 2016, 37(3):74-80. [11] 孙德山.支持向量机分类与回归方法研究[D].长沙:中南大学,2004.SUN D S. The researches on support vector machine classification and regression methods[D]. Changsha:Central South University, 2004. [12] 季凯敏,路川藤.长江口外潮汐精细化模型研究与精度分析[J].海洋技术学报, 2019, 38(5):64-67.JI K M, LU C T. Research and precision analysis on the tide model outside the Yangtze River estuary[J]. Journal of Ocean Technology, 2019, 38(5):64-67. |
|
服务与反馈:
|
|
【文章下载】【发表评论】【查看评论】【加入收藏】
|
|
|