| 1. | Cgts coast and geodetic tide station
海岸与大地潮汐测量站 |
| 2. | Coast and geodetic tide station
海岸与大地潮汐测量站 |
| 3. | Secondary tide station
次要验潮站 |
| 4. | The times and heights of the maximum sea level and maximum storm surge recorded at various tide stations in hong kong
香港各潮汐测量站录得的最高潮位及最大风暴潮；及 |
| 5. | F the times and heights of the maximum sea level and maximum storm surge recorded at various tide stations in hong kong
F香港各潮汐测量站录得的最高潮位及最大风暴潮及 |
| 6. | Times and heights of the maximum sea level and the maximum storm surge recorded at tide stations in hong kong during the passage of sanvu
珊瑚影响香港期间，香港各潮汐站所录得的最高潮位及最大风暴潮 |
| 7. | Times and heights of the maximum sea level and the maximum storm surge recorded at tide stations in hong kong during the passage of damrey
达维影响香港期间，香港各潮汐站所录得的最高潮位及最大风暴潮 |
| 8. | Times and heights of the maximum sea level and the maximum storm surge recorded at tide stations in hong kong during the passage of vicente
韦森特影响香港期间，香港各潮汐站所录得的最高潮位及最大风暴潮 |
| 9. | Times and heights of the maximum sea level and the maximum storm surge recorded at tide stations in hong kong during the passage of damrey
表3 . 3 . 3达维影响香港期间，香港各潮汐站所录得的最高潮位及最大风暴潮 |
| 10. | Starting with the astronomic factors which induce the tide phenomenon , this paper introduces a method of nonharmonic analysis neural network to predict tide , and this method is used to calculate the real tide of 2002 at hongkong tide station and the result are compared to the observed data
摘要文章运用非调和法，直接从引起潮汐现象的天文因素入手，以2002年香港验潮站实测资料为例，用神经网络对潮汐知识进行了学习仿真，对未知结果进行了预报。 |
