data pattern造句
例句與造句
- It sketches an outline of the data pattern more clearly .
它對資料模型的輪廓描繪得更清晰。 - Trigger on data patterns within a spi frame
在spi幀內(nèi)的特定數(shù)據(jù)碼型上觸發(fā)在i - Trigger on address and or data patterns within an i2c frame
C幀內(nèi)的特定地址和或數(shù)據(jù)上觸發(fā) - These numbers are sensitive to the data pattern of the existing data and of the data to be loaded
這些數(shù)字與現(xiàn)有數(shù)據(jù)及要加載的數(shù)據(jù)的數(shù)據(jù)樣式相關(guān)。 - Commands to set data patterns , perform ecc tests , manipulate the error log , dump the sequencer ram
用來為測試配置柱面，磁頭，給出選項來隨機(jī)柱面/磁頭和隨機(jī)數(shù)據(jù)模式的指令。 - It's difficult to find data pattern in a sentence. 用data pattern造句挺難的
- Spi triggering allows for trigger on user - definable framing and user - definable number of bits per frame , as well as data patterns
Spi允許在用戶義幀,用戶俯定義的每幀比特數(shù)以及數(shù)據(jù)碼型上觸發(fā) - Simple , programmatically controlled xml or relational database getting and setting , is useful when only a trivial algorithm is required , but the data pattern is still too complex for datapool generated inputs
簡單的說，當(dāng)只需要一般演算法時，透過程式設(shè)計方法控制的xml或關(guān)聯(lián)資料庫的獲取和設(shè)定是有用的，但資料樣式對于產(chǎn)生的資料池輸入仍舊是太復(fù)雜。 - In this paper , we propose a scheme to solve the problem of outlier data patterns that the value of outlier data pattern is deleted first and then is predicted by the model of genetic algorithm and neural network
對于數(shù)據(jù)集中的異常樣本值，本文提出了一種解決方案：先刪除異常的屬性值，然后再用遺傳bp神經(jīng)網(wǎng)絡(luò)模型進(jìn)行預(yù)測填補(bǔ)，通過實驗證明這種方案的可行性。 - It consists of demanding analysis , system structure , data flowing diagram , function module and the application of key techniques , takes and organizes offer parameter and data , uses entity - relation ( e - r ) pattern to design data pattern , selects ms sql server 7 as database , founds database physical structure
說明了基于c s和b s混合結(jié)構(gòu)模式的設(shè)計與實現(xiàn)，包括系統(tǒng)的需求分析，系統(tǒng)的解決方案，系統(tǒng)的體系結(jié)構(gòu)、數(shù)據(jù)流圖、功能模塊圖以及各關(guān)鍵技術(shù)的應(yīng)用。 - Discovering association rules is one of the most important task in data mining , that is to find interesting association or correlation relationships among a large set of data items . with massive amounts of data continuously being collected and stored , data patterns hidden in large data sets are more difficult to find
數(shù)據(jù)挖掘的一個重要的任務(wù)就是發(fā)現(xiàn)數(shù)據(jù)庫中的關(guān)聯(lián)規(guī)則，也就是發(fā)現(xiàn)數(shù)據(jù)項中項集之間有價值的關(guān)聯(lián)或相關(guān)聯(lián)系。隨著大量數(shù)據(jù)不停地收集和存儲，隱藏在數(shù)據(jù)項集中的數(shù)據(jù)模式也越來越難發(fā)現(xiàn)。 - Also , its electrical quality and bus topology are mastered as well as the differences among the four data flow types that consist of data pattern , transmitting direction , the capacity limitation of data pocket , and the bus interview confinement the design and test of hardware circuit with usb interface are finished
掌握其電氣連接特性、拓?fù)浣Y(jié)構(gòu)及四種傳輸方式在數(shù)據(jù)格式、數(shù)據(jù)包容量、總線訪問限制等方面各自不同的特征。 2 .進(jìn)行了系統(tǒng)硬件電路的設(shè)計與調(diào)試。 - The kanerva ' s sparse distributed memory ( sdm ) tackles the problem of training large data patterns and extendes the storage mode of existing computer . but it ' s address array produced randomly ca n ' t reveal the distribution of patterns and it has ' t the ability of function approximation for its learning rule
Kanerva的稀疏分布存儲( sdm )模型解決了大維數(shù)樣本的訓(xùn)練問題，推廣了現(xiàn)有計算機(jī)的存儲方式。但其地址矩陣的隨機(jī)預(yù)置方式不能反映樣本的分布，并且sdm的學(xué)習(xí)方式使之不能用于函數(shù)逼近及時間序列預(yù)測問題。 - One of the pioneering projects here was one that jim gray at microsoft research did looking at how different databases with astronomical data could be brought together so that a researcher who wanted to pose a theory or explore data patterns about observations of different galaxies could do that without going to each of those individual databases
一那在這里提倡計畫是他哪一吉姆在研究做看著的微軟變灰色有天文學(xué)的數(shù)據(jù)不同的數(shù)據(jù)庫可以如何被一起帶來以便一個研究員想要擺姿勢一個理論或者探究數(shù)據(jù)式樣有關(guān)不同的銀河觀察的事可以不去每一個那些個別的數(shù)據(jù)庫而做那。