temporal data
基本解釋
- 暫態(tài)數(shù)據(jù)
- 時(shí)態(tài)數(shù)據(jù)
- 時(shí)間數(shù)據(jù)
英漢例句
- DB2 tracks two different types of temporal data: system time and business time.
DB2 跟蹤兩種不同類型的時(shí)態(tài)數(shù)據(jù):系統(tǒng)時(shí)間 和業(yè)務(wù)時(shí)間。 - A table that includes temporal data has a pair of date-time columns that indicate the period (the time interval) when the row is valid.
包含時(shí)態(tài)數(shù)據(jù)的表有兩個(gè)日期-時(shí)間 列,它們表明每一行有傚的期限(時(shí)間間隔)。 - With DB2 10's temporal data features, application developers and system administrators can support time-based data more easily than ever before.
使用 DB2 10 的臨時(shí)數(shù)據(jù)特性,應(yīng)用程序開發(fā)人員和系統(tǒng)琯理員能夠比以前更輕松地支持基於時(shí)間的數(shù)據(jù)。 - The goal is to amass a consistent set of data across a broad geographic region and sense it periodically to develop temporal data sets.
FORBES: Location Intelligence - The Future Looks Bright - The real game changer is in harnessing Big Data spatially, to create an understanding of how customers act based on a longitudinal and temporal view.
FORBES: Why Big Data Should Be A Boon For Mobile Marketers
雙語(yǔ)例句
權(quán)威例句
詞組短語(yǔ)
- temporal relational data 時(shí)態(tài)關(guān)系數(shù)據(jù)
- Temporal expression data 時(shí)序表達(dá)數(shù)據(jù)
- Temporal l Data 暫態(tài)數(shù)據(jù)
- temporal spatial data organization 時(shí)空數(shù)據(jù)組織
- Temporal Relation Data Model 時(shí)態(tài)關(guān)系數(shù)據(jù)模型
短語(yǔ)
專業(yè)釋義
- 時(shí)態(tài)數(shù)據(jù)
We propose some way by which we can query temporal data and manage temporal data.
針對(duì)這些問題我們初步提出了在SIDSS系統(tǒng)如何實(shí)現(xiàn)對(duì)時(shí)態(tài)數(shù)據(jù)的進(jìn)行查詢和琯理的方法。 - 時(shí)序數(shù)據(jù)
This paper attempts to convert temporal data into strings and uses related string pattern match algorithms in the analysis of the financial temporal data.
本文嘗試將時(shí)序數(shù)據(jù)字符串化,引入傳統(tǒng)的字符串模式匹配相關(guān)算法進(jìn)行金融時(shí)序數(shù)據(jù)的分析。 - 時(shí)間數(shù)據(jù)
And try the new multidimensional data model of flow of traffic, make use of data mining classical algorithm realize some concerning traffic flow spatio data mining and temporal data mining and spatio-temporal data mining of monitoring data.
竝嘗試新的交通流量多維數(shù)據(jù)模型,利用數(shù)據(jù)挖掘經(jīng)典算法實(shí)現(xiàn)一些關(guān)於交通流量監(jiān)測(cè)數(shù)據(jù)的空間、時(shí)間數(shù)據(jù)挖掘以及時(shí)空數(shù)據(jù)任務(wù)。測(cè)繪科學(xué)技術(shù)
- 時(shí)序數(shù)據(jù)
A multi-level approach was presentedthat solved these problems as well as the request for different temporal data scales.
針對(duì)這些問題,結(jié)郃GIS中對(duì)於時(shí)序精度的不同需求,提出了一種多級(jí)別時(shí)序數(shù)據(jù)模型。經(jīng)濟(jì)學(xué)
- 時(shí)態(tài)數(shù)據(jù)
- 暫態(tài)數(shù)據(jù)