These data consist of scalar data ( temperature , pressure , etc ) and vector data ( velocity , etc ) , which are commonly defined on unstructured grids with complex topology 这些数据类型比较复杂,既有温度、压力等标量数据,又有速度等矢量数据,而且它们通常定义在非规则网格上的拓扑关系也很复杂。
What the practical problems is often gotten is a single variable time series which has a time interval of t , reflect by a lot of interactive physics factor , containing the mark of all variates participating in movement , traditional time series analysis is to analyse going from this array to the form directly it ' s time develops , one dimension analysis loses useful information , the characteristics of phase space reconstruction method is to construct one dimension scalar quantity to high dimension vector , prop the geometry space of the state , show all dynamical information of system in phase space . the characteristic that just constructs again according to the phase space in this text , analyse the time series of responding , use the relevant knowledge of symbol dynamics and reconstruct phase space , put forward a kind of relation degree analysis method of the systematic mathematics model which has theory basis , so reach the correction of calculation mathematics model , make it accord with the actual systematic state 实际问题中常常得到的是一个时间间隔为t的单变量的时间序列,它是许多物理因子相互作用的综合反映,蕴藏着参与运动的全部变量的痕迹,传统的时序分析是直接从这个序列去形式地分析它的时间演变,一维分析必然丧失许多有用信息,相空间重构方法的特点是把一维标量数据构造成高维矢量,支起状态的几何空间,在相空间中展示系统全部动力信息。本文正是根据相空间重构的特点,对响应时间序列进行分析,利用符号动力学、重构相空间等方法,提出一种有理论依据的系统数学模型关联度分析方法,从而达到修正计算数学模型,使其更符合实际系统状态的目的。
标量: scalar; invariant; scalar qu ...数据: data; record; information效标量数: criterion measure; criterion score标量数组运算: scalar array operation; scalar-array operation大量数据 海量数据: massdata测量数据: measured data; measurement data; measuring data; metric data; metrical data; o erveddata; observed data; survey data测量数据库: measurement data base; measurement database大量数据: large amounts of data; large sets of data; ma data; mass data; mass of data; massive data定量数据: quantitative data度量数据: measurement data度量数据库: metrics database多变量数据: multivariate data海量数据: a huge quantity of data; huge quantities of data; mass data话务量数据: traffic data计量数据: continuous data; measurement data库存量数据: inventory data流量数据: data on flows能量数据: energy datum实变量数据: real variable data矢量数据: vector data通信量数据: traffic data微剂量数据: microdosimetric data增量数据: incremental data变量数据类型: data type of a variable测量数据处理: measurement and data processing