懲罰訓練 的英文怎麼說

中文拼音 [chéngxùnliàn]
懲罰訓練 英文
punishment training
  • : 動詞1. (處罰) punish; penalize 2. [書面語] (警戒) take or give warning
  • : Ⅰ動詞[書面語] (處罰) punish; penalize; fine; forfeit Ⅱ名詞(處罰) punishment; penalty
  • : Ⅰ動詞1 (教導; 訓誡) lecture; teach; train 2 (解釋) explainⅡ名詞1 (準則) standard; model; ex...
  • : 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...
  • 訓練 : train; drill; manage; practice; breeding
  1. The museum, inside the correctional services staff training institute, features a mock gallows, two imitation cells and stylised guard tower on top of the building. nine galleries feature some 600 artifacts and exhibits covering the history and development of the prison system, punishment and imprisonment, staff uniforms and insignia, vietnamese boat people, homemade weapons and more. there is a souvenir shop on the g f selling items like badges

    博物館位於教署職員學院內,館內設有九間展覽室,展出600餘件與香港教服務有關的文物,包括一座模擬絞刑臺和兩間模擬囚室,屋頂更設有模擬監獄瞭望塔,記載了香港教制度刑,以及教人員制服徽號等的歷史和演變過程。
  2. The primary missions of the russian spetsnaz are : acquiring intelligence on major economic and military installations and either destroying them or putting them out of action, organizing sabotage and acts of subversion ; carrying out punitive operations against rebels ; forming and training insurgent detachments, etc

    俄羅斯特殊任命部隊的主要任務是:獲得重要經濟和軍事基地的情報並破壞或消滅這些經濟和軍事基地,組織破壞和顛覆行動;對反叛者執行性的行動;建立和起義部隊等等。
  3. The algorithms for training weights update and constructing the target vectors are discussed. use the penalty term to improve the astringency of network. and study how choice the appropriate initial weights

    著重研究了根據輸入和輸出量合理選擇網路結構,權值的更新演算法,目標向量的合理構造,帶項的bp網路,改善了網路的收斂性。
  4. The second stage was from 1904 to 1912. the qing government decided to train the new army in the whole nation, such as how to train the army, reward the students, the introduction of the rank and medal, the new pension system and the regulations of

    第二階段,清政府決定在全國展新軍,對新軍、軍校學生的獎勵及軍銜制、勛章制的引進,新的恤賞制度,和《陸軍專章》等一系列法規的制定,使得這一階段的獎制度充滿了近代的氣息。
  5. Define a radial basis function ( rbf ) at center of each cluster and learning a two - layer neural network which consists of these rbfs, simultaneously, for the purpose of avoiding over - fitting, we make use of ridge regression method, which adding a weight penalty term including a appropriate regularization parameter on the cost function and then lead to a more smooth function

    為每一個簇的中心定義相應的徑向基函數( radialbasisfunction , rbf ) ,再對這些徑向基函數構成的兩層神經網路進行,同時,為了避免產生過度擬合現象,本文採用了嶺回歸技術,即在代價函數中加入一個包含適當正規化參數的權值項,從而保證網路輸出函數具有一定的平滑度。
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