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TranslationMobile

機械原理

"theory" in Chinese : n. 1.理論，學理，原理。 2.學說，論說 (opp. ...
"machine" in Chinese : n. 1.機(器)，機械；機關，機構。 2.印刷機器；縫 ...
"theory of machines and mechanisms" in Chinese : 機械原理
"machines" in Chinese : 機器; 馬奇內斯; 裝配機床
"and theory" in Chinese : 經(jīng)驗與理論，119
"in theory" in Chinese : 從理論上說; 理論上，理論上講
"s theory" in Chinese : 弗洛倫斯學說; 戈爾茨學說; 赫伯理論; 嘉農(nóng)氏理論
"the theory of the" in Chinese : 事業(yè)理論
"theory" in Chinese : n. 1.理論，學理，原理。 2.學說，論說 (opp. hypothesi ...
"theory of" in Chinese : 經(jīng)驗的理論，6
"will theory" in Chinese : 意思說
"a theatre of machines" in Chinese : 壞圖解手冊; 機械圖解手冊
"accessories for machines" in Chinese : 機器零件
"accounting machines" in Chinese : 會計機器; 會計計算機器
"agricultural machines" in Chinese : 農(nóng)業(yè)機械

Examples

Terminology for the theory of machines and mechanisms
機器理論與機構學術語
Quality education and reform in teaching theory of machines and mechanisms
素質教育與機械原理教學改革
However , this is depend on the accurate simulation on nonlinear transient electromagnetic field , which relate with many aspects , include transient theory of machine , numerical calculation method , solving nonlinear equations , fem mesh generation and so on
但是，這首先要依賴于對電機非線性瞬態(tài)過程的準確仿真，涉及到從電機的瞬態(tài)過程理論、數(shù)值計算方法、乃至非線性方程組求解和有限元剖分等多方面的問題。
With vrml techniques , the process of co - rotating twin - screw machining is simulated based on the theory of machining with milling cutter , and the machining simulation theory and its key techniques are discussed . the mathematic model and computation are proved correct and feasible through cutting experiment and the model is now applied in practice
該方法和技術可以有效的支持同向雙螺桿圓柱螺旋面的加工刀具的優(yōu)選。并在用圓柱立銑刀加工同向雙螺桿的理論基礎上，利用vrml技術，對加工過程及其理論誤差進行了仿真，討論了仿真加工的原理和關鍵技術。
Because of ineffectiveness of naive bayes model for text classification , this thesis proposed integrating boosting theory of machine learning in classification process , boost naive bayes categorization model through many times training . improved by experiments , mutual information and naive bayes integrated with boosting bring very good precision , recall , and f1 score
鑒于樸素貝葉斯的分類效果不佳，本論文又提出將機器學習中的boosting思想結合到樸素貝葉斯的分類模型中，對樸素貝葉斯模型進行提升，實驗證明，改進的互信息和給合了boosting思想的樸素貝葉斯分類模型均產(chǎn)生良好的分類效果?分準率、分全率及f1值。