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| 1 | A precise tidal prediction mechanism based on the combination of harmonic analysis and adaptive network-based fuzzy inference system model显示文摘An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system(ANFIS)model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules: the astronomical tide module caused by celestial bodies' movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system(FIS) structure,three approaches which include grid partition(GP), fuzzy c-means(FCM) and sub-clustering(SC) are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability. | ZHANG Zeguo YIN Jianchuan WANG Nini HU Jiangqiang WANG Ning | 2017 | Acta Oceanologica Sinica2017，36，11： | 6 |
| 2 | 基于灰色马尔可夫模型的钱塘江高潮位预测显示文摘钱塘江高潮位符合海潮变化规律的同时,更容易受到水文、气象等因素影响.针对潮位预报难、预报精度低的问题,通过对2001—2010年钱塘江历史高潮位数据的分析和研究,将灰色系统理论与马尔可夫链结合,建立了灰色马尔可夫潮位残差修正预测模型.利用灰色预测模型对未来的潮位进行预测,并对预测结果用马尔可夫链进行修正,以提高预测精度.该模型预测了钱塘江盐官水文站2011—2012年农历八月十八的高潮位,并与实测高潮位数据和现用的预报方法进行对比,验证了灰色马尔可夫模型在钱塘江高潮位预测中具有较高的精度. | 王瑞荣 陈浩龙 薛楚 孙映宏 | 2016 | 杭州电子科技大学学报(自然科学版)2016，36，2： | 2 |
| 3 | 基于离散小波变换与时间序列的钱塘江潮位预测显示文摘针对钱塘江潮位呈现出的周期性、随机性和波动性,为实现对钱塘江潮位的有效预测,提出一种基于离散小波变换和时间序列的预测方法,即先利用离散小波变换将实测的钱塘江潮位序列进行分解与重构,将非平稳的序列转化为多层较平稳的序列;然后利用时间序列建模方法对分解后的各个序列分别建立时间序列模型,对各层进行动态预测;最后将各层预测值求和作为最终的预测结果。试验表明,所提方法预测的效果明显优于其他混合模型及单一模型,能够提供更加准确的潮位预测。 | 王培力 王瑞荣 高鹏 朱广明 余小庆 孙映宏 | 2016 | 水电能源科学2016，34，6： | 1 |
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