AIS数据挖掘对马六甲海峡潮波特征的初步研究

Q4 Engineering Disaster Advances Pub Date : 2023-06-15 DOI:10.25303/1607da0107
M. Mustaffa, Aini Nazli Ahmad, Shaharudin Ahmad
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引用次数: 0

摘要

本研究采用先进的数据挖掘技术和自动识别系统(AIS)数据对马六甲海峡的潮汐和波浪动力学进行了研究。几个世纪以来,这条海峡一直是连接印度洋、南中国海和太平洋的重要商业路线。它位于苏门答腊岛东海岸和马来西亚半岛西海岸之间,东南端有新加坡海峡。这项研究的初步发现表明,船只坐标的距离与潮汐时间之间有很强的相关性,而潮汐时间主要受到太阳和月亮和谐运动的影响。通过AIS数据挖掘和分析,本研究展示了在潮汐事件期间预测海平面高度的潜力。这些结果可以在未来的研究中进一步探索。总的来说,这项研究为了解世界上最长海峡复杂的潮汐和波浪动力学提供了宝贵的见解,并强调了AIS数据挖掘对提高我们对海洋现象的认识的前景。研究结果可能有助于开发更精确有效的方法来预测海平面高度和预测其他海洋过程。
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Preliminary study on Strait of Malacca Tide Wave Characteristic from AIS Data Mining
In this study, advanced data mining techniques and Automatic Identification System (AIS) data were used to examine the tidal and wave dynamics of the Strait of Malacca. This strait has been an important commercial route for centuries, connecting the Indian Ocean to the South China Sea and the Pacific Ocean. It is located between Sumatra Island's east coast and Peninsular Malaysia's west coast, with the Strait of Singapore at its southeast end. The study's initial findings indicate a strong correlation between the distance of ships' coordinates and the timing of the tide, which is mainly influenced by the harmonic motion of the sun and the moon. Through AIS data mining and analysis, this study demonstrates the potential for predicting sea heights during tidal events. These results could be further explored in future research. Overall, this study offers valuable insights into the intricate tidal and wave dynamics of the world's longest strait and highlights the promise of AIS data mining for advancing our knowledge of oceanic phenomena. The research outcomes could potentially facilitate the development of more precise and effective methods for forecasting sea heights and predicting other marine processes.
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来源期刊
Disaster Advances
Disaster Advances 地学-地球科学综合
CiteScore
0.70
自引率
0.00%
发文量
57
审稿时长
3.5 months
期刊介绍: Information not localized
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