Extreme waves have a profound impact on coastal infrastructure;thus,understanding the variation law of risky analysis and disaster prevention in coastal zones is necessary.This paper analyzed the spatiotemporal charac...Extreme waves have a profound impact on coastal infrastructure;thus,understanding the variation law of risky analysis and disaster prevention in coastal zones is necessary.This paper analyzed the spatiotemporal characteristics of extreme wave heights adjacent to China from 1979 to 2018 based on the ERA5 datasets.Nonstationary extreme value analysis is undertaken in eight repre-sentative points to investigate the trends in the values of 50-and 100-year wave heights.Results show that the mean value of extreme waves is the largest in the eastern part of Taiwan Island and the smallest in the Bohai Sea from 1979 to 2018.Only the extreme wave height in the northeastern part of Taiwan Island shows a significant increase trend in the study area.Nonstationary analysis shows remarkable variations in the values of 50-and 100-year significant wave heights in eight points.Considering the annual mean change,E1,E2,S1,and S2 present an increasing trend,while S3 shows a decreasing trend.Most points for the seasonal mean change demon-strate an increasing trend in spring and winter,while other points show a decreasing trend in summer and autumn.Notably,the E1 point growth rate is large in autumn,which is related to the change in typhoon intensity and the northward movement of the typhoon path.展开更多
Field and laboratory observations indicate that the variation of drag coefficient with wind speed at high winds is different from that under low-to-moderate winds.By taking the effects of wave development and sea spra...Field and laboratory observations indicate that the variation of drag coefficient with wind speed at high winds is different from that under low-to-moderate winds.By taking the effects of wave development and sea spray into account,a new parameterization of drag coefficient applicable from low to extreme winds is proposed.It is shown that,under low-to-moderate wind conditions so that the sea spray effects could be neglected,the nondimensional aerodynamic roughness first increases and then decreases with the increasing wave age;whereas under high wind conditions,the drag coefficient decreases with the increasing wind speed due to the modification of the logarithmic wind profile by the effect of sea spray droplets produced by bursting bubbles or wind tearing breaking wave crests.The drag coefficients and sea surface aerodynamic roughnesses reach their maximum values vary under different wave developments.Correspondingly,the reduction of drag coefficient under high winds reduces the increasing rate of friction velocity with increasing wind speed.展开更多
针对推荐算法的信息过期问题,结合遗忘函数和信息保持期的改进时间权重引入矩阵分解模型,提出一种基于改进时间权重的矩阵分解协同过滤算法(MFTWCF,MF-based and improved time weighted collabora tive filtering),相比前人提出的基于...针对推荐算法的信息过期问题,结合遗忘函数和信息保持期的改进时间权重引入矩阵分解模型,提出一种基于改进时间权重的矩阵分解协同过滤算法(MFTWCF,MF-based and improved time weighted collabora tive filtering),相比前人提出的基于改进时间权重的邻域协同过滤算法(NTWCF,neighborhood-based and improved time weighted collaboratire filering algorithm),准确性显著提升了26.58%。由于过去的信息所包含的特征在随后的时间里可能被用户持续关注,从而增强过期信息对推荐的影响力,所以提出了融合时间权重和类型影响力加强权重的改进算法(MFTTWCF,MF-bosed and imporved time and type weighteel collaborative filtering)修正上述时间权重。电影数据集的实验证明,MFTTWCF算法预测的准确性比MFTWCF算法提高了3.58%,能够取得更好的推荐效果,适用于通过预测评分进行推荐的系统。展开更多
基金support of the Natural Science Foundation of China(No.51909114)the Major Research Grant(Nos.U1806227,U1906231)from the National Natural Science Foundation of China(NSFC).
文摘Extreme waves have a profound impact on coastal infrastructure;thus,understanding the variation law of risky analysis and disaster prevention in coastal zones is necessary.This paper analyzed the spatiotemporal characteristics of extreme wave heights adjacent to China from 1979 to 2018 based on the ERA5 datasets.Nonstationary extreme value analysis is undertaken in eight repre-sentative points to investigate the trends in the values of 50-and 100-year wave heights.Results show that the mean value of extreme waves is the largest in the eastern part of Taiwan Island and the smallest in the Bohai Sea from 1979 to 2018.Only the extreme wave height in the northeastern part of Taiwan Island shows a significant increase trend in the study area.Nonstationary analysis shows remarkable variations in the values of 50-and 100-year significant wave heights in eight points.Considering the annual mean change,E1,E2,S1,and S2 present an increasing trend,while S3 shows a decreasing trend.Most points for the seasonal mean change demon-strate an increasing trend in spring and winter,while other points show a decreasing trend in summer and autumn.Notably,the E1 point growth rate is large in autumn,which is related to the change in typhoon intensity and the northward movement of the typhoon path.
基金supported by the National Key R&D Program of China(No.2018YFB1501901)the National Natural Science Foundation of China(Nos.51909114,U1806227 and U1906231)the Guangxi Key Laboratory of Marine Environmental Science,Guangxi Academy of Sciences(No.GXKLHY21-04).
文摘Field and laboratory observations indicate that the variation of drag coefficient with wind speed at high winds is different from that under low-to-moderate winds.By taking the effects of wave development and sea spray into account,a new parameterization of drag coefficient applicable from low to extreme winds is proposed.It is shown that,under low-to-moderate wind conditions so that the sea spray effects could be neglected,the nondimensional aerodynamic roughness first increases and then decreases with the increasing wave age;whereas under high wind conditions,the drag coefficient decreases with the increasing wind speed due to the modification of the logarithmic wind profile by the effect of sea spray droplets produced by bursting bubbles or wind tearing breaking wave crests.The drag coefficients and sea surface aerodynamic roughnesses reach their maximum values vary under different wave developments.Correspondingly,the reduction of drag coefficient under high winds reduces the increasing rate of friction velocity with increasing wind speed.
文摘针对推荐算法的信息过期问题,结合遗忘函数和信息保持期的改进时间权重引入矩阵分解模型,提出一种基于改进时间权重的矩阵分解协同过滤算法(MFTWCF,MF-based and improved time weighted collabora tive filtering),相比前人提出的基于改进时间权重的邻域协同过滤算法(NTWCF,neighborhood-based and improved time weighted collaboratire filering algorithm),准确性显著提升了26.58%。由于过去的信息所包含的特征在随后的时间里可能被用户持续关注,从而增强过期信息对推荐的影响力,所以提出了融合时间权重和类型影响力加强权重的改进算法(MFTTWCF,MF-bosed and imporved time and type weighteel collaborative filtering)修正上述时间权重。电影数据集的实验证明,MFTTWCF算法预测的准确性比MFTWCF算法提高了3.58%,能够取得更好的推荐效果,适用于通过预测评分进行推荐的系统。
