为构建更接近真实的高分辨率三维海底地形,满足舰船安全高效航行及水下地形匹配导航需求,运用迭代函数系统(IFS,iterated function system)分形插值方法,对原始网格水深数据样本,根据其密度及震荡程度的差异,调节不同的垂直比例因子得...为构建更接近真实的高分辨率三维海底地形,满足舰船安全高效航行及水下地形匹配导航需求,运用迭代函数系统(IFS,iterated function system)分形插值方法,对原始网格水深数据样本,根据其密度及震荡程度的差异,调节不同的垂直比例因子得到细化的分形插值结果,以描述海底地形的起伏变化。仿真结果表明,对于平坦或缓坡海底地形,垂直比例因子在[0.05,0.2]区间构建结果能兼顾海底地貌的自相似与光滑要求;对于高频震荡海底地形,垂直比例因子在[0.3,0.5]区间构建结果牺牲一定光滑度条件下更能正确处理海底地形全貌与局部之间的关系,高度逼近海底地形自然地貌。样本数据均匀抽稀后,调节垂直比例因子,构建结果整体上可以与原始样本高度逼近,尤其在震荡剧烈的海底地形构建中具有优越性。展开更多
In light of rapid development of customer requirements, control procedures of quality concept use multivariate analysis. This is because of recent advances in information technology and in recording. The charting proc...In light of rapid development of customer requirements, control procedures of quality concept use multivariate analysis. This is because of recent advances in information technology and in recording. The charting procedures are based on Mahalanobis distance but their performance needs normality and a type-I error rate choice. The DD-diagram is an alternative scheme that uses data depth to avoid these conditions rarely met in practice. For a given error-free sample, the performance of DD-diagram and that of multivariate EWMA control procedures are compared through a real example on individual observations taken from a multivariate quality process.展开更多
文摘为构建更接近真实的高分辨率三维海底地形,满足舰船安全高效航行及水下地形匹配导航需求,运用迭代函数系统(IFS,iterated function system)分形插值方法,对原始网格水深数据样本,根据其密度及震荡程度的差异,调节不同的垂直比例因子得到细化的分形插值结果,以描述海底地形的起伏变化。仿真结果表明,对于平坦或缓坡海底地形,垂直比例因子在[0.05,0.2]区间构建结果能兼顾海底地貌的自相似与光滑要求;对于高频震荡海底地形,垂直比例因子在[0.3,0.5]区间构建结果牺牲一定光滑度条件下更能正确处理海底地形全貌与局部之间的关系,高度逼近海底地形自然地貌。样本数据均匀抽稀后,调节垂直比例因子,构建结果整体上可以与原始样本高度逼近,尤其在震荡剧烈的海底地形构建中具有优越性。
文摘In light of rapid development of customer requirements, control procedures of quality concept use multivariate analysis. This is because of recent advances in information technology and in recording. The charting procedures are based on Mahalanobis distance but their performance needs normality and a type-I error rate choice. The DD-diagram is an alternative scheme that uses data depth to avoid these conditions rarely met in practice. For a given error-free sample, the performance of DD-diagram and that of multivariate EWMA control procedures are compared through a real example on individual observations taken from a multivariate quality process.
