間斷性訓練 的英文怎麼說

中文拼音 [jiānduànxìngxùnliàn]
間斷性訓練 英文
short rest training
  • 間 : 間Ⅰ名詞1 （中間） between; among 2 （一定的空間或時間里） with a definite time or space 3 （一間...
  • 斷 : Ⅰ動詞1 （分成段） break; snap 2 （斷絕;隔斷） break off; cut off; stop 3 （戒除） give up; abstai...
  • 性 : Ⅰ名詞1 （性格） nature; character; disposition 2 （性能; 性質） property; quality 3 （性別） sex ...
  • 訓 : Ⅰ動詞1 （教導; 訓誡） lecture; teach; train 2 （解釋） explainⅡ名詞1 （準則） standard; model; ex...
  • 練 : Ⅰ名詞1 （白絹） white silk 2 （姓氏） a surname Ⅱ動詞1 （加工處理生絲） treat soften and whiten s...
  • 間斷 : be disconnected; be interrupted; interval; leapfrogging; disjunction; break hiatus; hiatus; inter...
  • 訓練 : train; drill; manage; practice; breeding
  1. Conversely, inconsistent training can lead to a variety of injuries

    相反地，間斷性的訓練將導致各種傷害。
  2. In the paper, based on the existing literature research foundation an analog circuit catastrophic fault location approach by using feedforward networks with back ? propagation learning is realized. by this approach, the simulation require ments before test are reduced because fewer training samples are needed, and the fault location process is fast. this method is very efficient in location of single hard fault wit component tolerances. the measureme nt space feature and the general characterization concept of single and double soft fault in linear circuits are presented. according to this concept, a linear circuits soft fault location approach using subhidden layer bpnn is established with element tolerance, and it is shown that this approach is successful in fault location. a double fault feature extraction.,

    本文在現有文獻理論研究的基礎上實現了採用bp演算法前向多層神經網路對直流測試下模擬電路硬故障的診斷方法。其特點是採用少量典型特徵樣本作為bp網路的訓練樣本，獲得訓練樣本的代價小，減少了測前工作量，同時診斷速度快，在考慮元件容差時仍有好的診斷效果。文中介紹了線性電路單一軟故障和雙軟故障所具有的電壓增量空間特性和統一特徵概念。
  3. First, the fault type is identified by rough - set, then the neural networks determines the fault elements by the sampling voltage values. with regarding to the other method, the rough - set is looked as the pre - system of neural network. the fault information as well as the sampling voltage values are simplified by rough - set, and the outcome of this processing is the input of neural network.

    整體結合是利用粗糙集對故障信息中樣本的所有故障徵兆進行數據處理，通過知識約簡，刪除多餘的徵兆屬性，簡化知識表達空間維數，簡化以後的樣本數據作為神經網路的訓練樣本，構成完整的粗糙集-神經網路故障診斷方法，將粗糙集與神經網路相結合，簡化了神經網路結構，從而達到提高診斷速度的目的。
  4. In order to diagnose complex system, because there exists too many characteristic parameters, the problems, such as over - large scale of neural network, unduly long train time, and redundant rules in expert system ' s rule base, will result in the reduction of whole system ' s practical performance. then the rough set theory that received focus attention in recent years is led into the internal - combustion engine fault diagnosis work. the application of this theory in the attributable optimization of fault diagnosis characteristic parameters is explored

    考慮到在對復雜系統進行診斷時，由於特徵參數過多而造成神經網路規模過大、訓練時間過長以及專家系統規則庫存在規則冗餘等問題，最終導致整個系統實用性能的降低，為此將粗糙集理論引入了內燃機故障診斷工作，對其在故障診斷特徵參數屬性優化中的運用進行了探索。
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