靜態次常式 的英文怎麼說

中文拼音 [jìngtàichángshì]
靜態次常式 英文
subroutine static
  • : Ⅰ形容詞1. (安定不動; 平靜) still; calm; motionless 2. (沒有聲響; 清靜) silent; quiet Ⅱ名詞(姓氏) a surname
  • : 名詞1. (形狀; 狀態) form; condition; appearance 2. [物理學] (物質結構的狀態或階段) state 3. [語言學] (一種語法范疇) voice
  • : Ⅰ名詞1 (次序; 等第) order; sequence 2 [書面語] (出外遠行時停留的處所) stopping place on a jou...
  • : 名詞1 (樣式) type; style 2 (格式) pattern; form 3 (儀式; 典禮) ceremony; ritual 4 (自然科...
  • 靜態 : [物理學] static state; quiescent condition; steady state; statics; dead level; akinesis; akynesis...
  1. The principle and the mechanical structure of the air - gap inductance - type transducer are analyzed in this article, and the static parameters are calibrated. dynamic calibration is applied to air - gap inductance - type transducer which is not good in dynamic capability, to obtain the dynamic parameters of the transducer and its measuring circuit. based on the result of the dynamic calibration, the transducer and its serving circuit are modeled so that the method of how to improve the dynamic performance can be found

    本文對現有氣隙電感傳感器在原理和機械結構上作了深入的分析,對其參數進行了標定;並且針對規電感傳感器動響應低,不宜用於快速動測量的缺點,引入測試系統動力學的思想,設計了一套動校準系統,對現有傳感器進行多校準,根據動校準的實驗結果對現有傳感器建立數學模型,得到現有傳感器的動特性;在此基礎上,根據磨床工件在線檢測的要求,設計一個硬體補償系統來提高整個測試系統的動特性。
  2. Aspect to association rules mining, constructing two mining modes : static mining and dynamic mining ; implementing two level mining : single - level mining and domain - level mining. about classification engineering, the mainstream classification techniques were compared through thoroughly experiments, and some improvement was made to decision tree toward the concrete problem, which make naids detect some new type attacks and this kind of capability embodies the advantage of anomaly detection over misuse detection ; incremental mining approach was put forward which detect one window data amount, instead of batch of tcp / ip record, which was very suitable to on - line mining and make naids be high real - time performance

    在關聯規則挖掘上,建立了兩種挖掘模挖掘模、動挖掘模;實施兩個層面上的挖掘:單層面挖掘、領域層面挖掘;在分類引擎的構建上,通過實驗綜合比較了主流分類技術,並針對具體問題對決策樹分類方法進行了應用上的改進,從而使得naids系統具備一定的檢測新類型攻擊的能力,而這個特性正是異檢測的優勢所在;所提出的增量挖掘方法由於每只監測一個窗口的數據量,而不是批量處理網路日誌,所以非適合在線挖掘,從而使得naids在實時性上有較好的性能表現。
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