適應性訓練 的英文怎麼說

中文拼音 [shìyīngxìngxùnliàn]
適應性訓練 英文
aacclimatization training
  • 適 : 形容詞1 （適合） fit; suitable; proper 2 （恰好） right; opportune 3 （舒服） comfortable; well Ⅱ...
  • 應 : 應動詞1 （回答） answer; respond to; echo 2 （滿足要求） comply with; grant 3 （順應; 適應） suit...
  • 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...
  • 適應性 : adaptability; flexibility
  • 適應 : suit; adapt; get with it; fit
  • 訓練 : train; drill; manage; practice; breeding
  1. Gathering fuzzy technique and model - identifying technique to processing research, fuzzy model - identifying technique, a intersecting science, has been come out, which has become hoto in this thesis, based on deeply researching the fuzzy unit - identifying and complete analysis on data of measuring well of the chandqing wushenqi district, the method of constructing self - adapting multi - dimension non - liner subjection degree function has been created without precedento based on the extraction of routine measuring well character parameters, and for adopting self - adapting method to carry through character compression, the model has been improved the performance and enhanced the convergence speed and sorted precision of the algorithm o the relation of measuring well information and the oiliness & gassiness of sandstones is fuzzy ? in the thesis, the law of max subjection degree has been studied and improved, and proved preferable effect in the practical application

    論文在提取一些常規測井特徵參數的基礎上，採用自適應方法對各變量多項式進行優選，減少了特徵參數間的相關性，突出了類別間的差異性，從而優化了模式的質量，提高了分類的精度。測井信息和砂體的儲集性之間的關系是帶有模糊性的，論文對模糊「最大隸屬原則」進行了研究和改進，並在實際應用中取得了較好的效果。論文成功研製了「自適應」的演算法和軟體? ?即通過對正確回判率的比較，然後對參數進行調節的辦法，可將模式「訓練」到最佳狀態。
  2. At first, the text is segmented to words and converted to a sequence of part - of - speech tags ; then based on the pos tags sequence parameters and phrase - break distance information from training, markov model is used to get the most likely phrase break sequence

    首先，文本進行分詞，並轉換為一列由詞性標記所組成的序列；然後使用馬爾可夫模型，利用人工標注數據庫訓練詞語連接處詞性標注序列的概率分佈和連接類型序列的距離信息，得到輸入的詞性標記序列對應的具有最大似然概率的連接類型序列，最後利用后處理規則進行適當的糾錯。
  3. Compared with the classical bp algorithm, robust adaptive bp algorithm possesses some advantages as following : ( 1 ) increasing the accuracy of the network training by means of using both the relative and absolute residual to adjust the weight values ; ( 2 ) improve the robustness and the network convergence rate through combining with the robust statistic technique by way of judging the values of the samples " relative residual to establish the energy function so that can suppress the effect on network training because of the samples with high noise disturbances ; ( 3 ) prevent entrapping into the local minima area and obtain the global optimal result owing to setting the learning rate to be the function of the errors and the error gradients when network is trained. the learning rate of the weights update change with the error values of the network adaptively so that can easily get rid of the disadvantage of the classical bp algorithm that is liable to entrap into the local minima areas

    與基本bp演算法相比，本文提出的魯棒自適應bp演算法具有以下優點： （ 1 ）與魯棒統計技術相結合，通過訓練樣本相對偏差的大小，確定不同訓練樣本對能量函數的貢獻，來抑制含高噪聲干擾樣本對網路訓練的不良影響，從而增強訓練的魯棒性，提高網路訓練的收斂速度； （ 2 ）採用相對偏差和絕對偏差兩種偏差形式對權值進行調整，提高了網路的訓練精度； （ 3 ）在採用梯度下降演算法對權值進行調整的基礎上，通過將學習速率設為訓練誤差及誤差梯度的特殊函數，使學習速率依賴于網路訓練時誤差瞬時的變化而自適應的改變，從而可以克服基本bp演算法容易陷入局部極小區域的弊端，使訓練過程能夠很快的「跳出」局部極小區域而達到全局最優。
  4. In this dissertation, two kinds of optimization, methods are proposed. firstly, only these linking weights corresponding to the control rules that affect the control performance significantly are updated in order to reduce the compute works and speed up the training progress. secondly, the updating step is adjusted adaptively in accordance with the error and the change of error of the system based on the t - s model to get better performance

    針對模糊神經網路控制器一般存在著在線權值調整計算量大、訓練時間長、過度修正權值可能導致系統劇烈振蕩等缺點，提出了兩種模糊神經網路控制器的優化方法：在線自學習過程中僅對控制性能影響大的控制規則相關的權值進行修正，以減小計算量，加快訓練速度；基於t - s模糊模型，根據偏差及偏差變化率大小動態自適應調節權值修正步長，抑制控制器輸出的劇烈變化，避免系統發生劇烈振蕩。
  5. According to the modern education theory, we should adopt the following tactics in teaching the concept of chemistry : 1. use the vivid visual image to let the students gain the knowledge of the concept ; 2. create the atmosphere and let the students take part in the formation of the concept of chemistry ; 3. revise the old knowledge while learning the new one to realize the assimilation of concept ; 4. proceed step by step, lead the students deepen and develop the concept ; 5. give prominence to the understanding of the key words of the concept, get deeper understanding ; 6. pay attention to the relation between the concepts ; 7. optimize the study strategy and enhance the cognition standard, i. e. in the teaching of the concept of chemistry, we must pay great attention to the usage of various kinds of teaching method, including visual experiment, visual language and cai courseware, in order to help the students to understand the concept ; use the question to stimulate students " thoughts, give free rein to students " corpus, and let the students take part in the teaching process actively ; guide the students to remember new concepts and the help of their old knowledge ; pay attention to the levels of the concept, deepen and develop the concept continuously, use various ways to strengthen the meaning of the key words, help the students to master the concepts connotation, and give a clear extension, guide the students to found the concept system

    也就是說，在化學概念的教學中，要注意充分運用各種直觀教學手段，包括實驗直觀、語言直觀和cai課件直觀，幫助學生理解概念；注意運用問題啟動學生思維，發揮學生的主體性，使學生積極參與教學過程；要指導學生利用原有認知結構中適當的概念圖式來學習新概念；注意概念教學的層次性，不斷深化和發展概念；注意通過各種方式強化概念中關鍵字、詞的意義，幫助學生準確把握概念的內涵，清晰界定概念的外延；注意引導學生在應用中建立概念系統，形成合理的概念結構。同時在概念教學中還要注重學習方法的傳授和學習策略的形成，進行適當的元認知訓練，優化學生的學習策略，提高其元認知水平。根據化學概念的教學策略，化學概念的基本教學程序為:創設問題情境，引入概念;組織問題解決，建立概念;引導知識整理，概念系統化;指導練習應用，概念具體化。
  6. Seitaridis also faces a race to be fit for the start of the new spanish season later this month

    而塞法伊里迪斯也將要面對錯過針對本月底即將開始的新賽季的西班牙足球甲級聯賽的一系列適應性訓練。
  7. The lighter training is greatly appreciated to the players. while they are not totally rested the easier pace and fun drills bring a new spring to everyone ' s steps

    適應性訓練深受球員的歡迎。當球員還沒有完全休息好的時候，讓他們小跑或者做些趣味性的活動可以提升他們的活力。
  8. Because these methods do not need not only the doa of the signal ' s and the array manifold but also signal waveform, the blind beamforming algorithms using cyclostationarity signal ' s properties are the genuine blind algorithms

    該方法既不需要知道來波方向和陣列流形，也不需要提供訓練數據，僅利用信號的循環平穩特性就可以實現真正意義上的盲自適應波束形成。
  9. Finally, a feedback control system of neural network was designed and a special learning method was produced to train the neural network which was applied in the non - linear model of semi - active suspension. the result of test showed ride comfort and handling was improved preferably after the control, and the semi - active suspension system harmonized the vehicle performance with the controller

    最後，設計了神經網路反饋控制系統，採用一種特殊學習（直接學習）方法對其進行訓練，並將其應用於半主動懸架非線性模型的模擬驗證，通過對多種路面激勵輸入條件下的模擬分析表明：該神經網路反饋控制系統可以較好地提高車輛的乘坐舒適性和操縱穩定性，採用這種神經網路反饋控制的半主動懸架，可以較好地協調車輛性能。
  10. The training of visual aesthetic and logic construction makes stereo images break away from the research of technology, and apply on future visual design with the most proper formation

    並輔以視覺美學與邏輯建構的訓練，使立體影像脫離技術性的探討，以最適切的形式應用於未來的視覺設計當中。
  11. Firstly, the paper, combining the characteristic of synchronous pulse bursts and inhibition with the modified pcnn model, presents a way of finding the foveation points in the images adaptively and effectively, and simulates the human vision system. secondly, pcnn is extended to pcnns, based on the properties of information couple and transmission, an algorithm that is used to fuse images of the same target got by several sensors to an image is presented to simulate the human vision system. thirdly, combining the properties of synchronous pulse bursts, capture, and transmission and competition of waves, the paper presents two ways of classification, one is an algorithm based on the properties of neuron to capture and inhibit to classify the data taking on any complex unlinear distribution robustly, the other is based on the restricted distance and modified of the former to remove the influence of inferior samples in classification ; fin ally, based on the accumulative difference pictures, and the forming and transmission of pcnn wave, selecting and controlling the direction of autowave by connecting the neighbouring neurons selectively, the paper presents a way to simulate the tracks of moving object and detect the moving direction

    首先結合pcnn的同步脈沖發放和側抑制特性，提出了基於改進型pcnn的圖像凹點檢測演算法，該演算法是一種自適應而有效的圖像凹點檢測方法，並且較好地模擬了人類視覺系統；然後，結合信息傳遞和信息耦合特性，將pcnn擴展成pcnns （ pcnn網路群） ，提出了一種基於pcnns的圖像融合演算法，能夠將多個傳感器獲取的同一目標的圖像信息融合到一幅圖像中，有效模擬了人類視覺系統；另外，結合pcnn的同步脈沖發放特性、捕獲特性和波的傳播競爭特性，開拓地將pcnn用於模式分類中，提出了基於耦合神經元點火捕獲抑制特性的分類方法和改進的約束距離下的pcnn分類方法，前者可實現對樣本空間中任意復雜分佈訓練樣本的穩健非線性分類，而後者能夠消除訓練樣本中刺點對分類的影響；最後，結合累積差分圖像思想、 pcnn波的形成與傳播特性，通過各神經元之間連接取向來選擇與控制自動波的流向，將pcnn用於運動視覺分析中的運動軌跡模擬及運動方向檢測。
  12. In this paper an artificial neural network ( ann ) approach, which is based on flexible nonlinear models for a very broad class of transfer functions, is applied for multi - spectral data analysis and modeling of airborne laser fiuorosensor in order to differentiate between classes of oil on water surface

    由於ann方法適合於處理非線性系統，具有自組織、自學習、自適應和聯想能力，故通過對樣本反復訓練，能辨別各類樣本特徵差異，本論文的核心工作就是將人工神經網路（ ann ）的方法應用於激光遙感光譜數據的智能分析。
  13. Lots of experiments are performed in this paper, the result of these experiments shows that the bl - ahmm model trained by ga - hmm model is effective and has better performance over the traditional hmm recognition method

    文中通過大量的試驗證明了採用ga - hmm訓練的bl - ahmm自適應模型的有效性和其相對傳統hmm識別模型的優越性。
  14. The emphasis of the article lies in the teaching tactics, i explain it from 7 steles : create circumstances, train thought, settle problem, develop " open problem ", try to discover an important mathematical fact, explore the mathematical experiments, cultivate the ability of study independently etc. with my suitable teaching cases, i expound teaching tactics on how to improve and also take point out some problems that we should pay much attention to

    本文的重點是在教學策略上，分別從「情境創設、訓練思維、問題解決、開放性問題教學、嘗試『發現』 、數學實驗、自學能力」等七個方面通過配以適當的教學案例，對如何提高學生主體參與意識作了詳細的闡述，同時也指出了在實際教學中應注意的問題。
  15. After phase 4, inspection and validation, the training center pi should coordinate with the corresponding air carrier pi if applicable, make an evaluation agreement on the training center regulation compliance, and submit this evaluation agreement to the regional administration flight standards office and the principal manager of the regional administration, make the decision of whether to issue the certificate or not, at the same time, apply for the certificate number of ccar - 142 training center to the flight standards department, the two character code of pinyin represent each administration, for example, hd represents east china regional administration, hb represents north china regional administration etc

    完成第四階段驗證檢查后，訓練中心主任監察員應當與相關航空承運人主任監察員進行協調如適用，就訓練中心規章符合性問題達成一致意見，並將此意見提交給地區管理局飛行標準處和管理局主管領導，做出是否頒證的決定，同時可以向飛行標準司申請ccar 142部訓練中心合格證代碼，其中漢語拼音的兩字代碼分別表示不同管理局，如hd代表華東管理局hb代表華北管理局等。
  16. Conclusion in this study, previously sedentary, overweight or obese postmenopausal women experienced a graded dose - response change in fitness across levels of exercise training

    結論：本研究中，以前久坐且超重或肥胖的絕經后婦女在健康訓練的各個適應性水平上，經歷了的一個分級的訓練強度反應實驗。
  17. Campared with statistical analyze, it is shown that, the network structure and network output after trained rbfnn using improved rols is more reasonable than k - mean algrithm, and the control model has the property of self _ learning, self _ organization and self _ adaptive, and the control precision can be more than 90 %. on the other hand, this paper also shows that, rbfnn model can control the desulfuration process on the whole in time, and the prediction result using rbfnn model is better than statistical analyze method

    同統計分析結果比較，得出以下結論：利用改進rols演算法訓練rbf網路比k -均值演算法能夠得到更加合理的網路結構和網路輸出；利用rbfnn所建立的脫硫智能控制模型具有自學習性、自組織性和自適應性，其控制精度達到90 %以上； rbf神經網路模型基本可以對脫硫過程進行及時控制；基於rbfnn模型的預測效果優于傳統的統計分析結果。
  18. Nonlinear dynamic modelling of sensors is an important aspect in the field of instrument technique. the recursive neural network is proposed for nonlinear dynamic modelling of sensors, as its architecture is determined only by the number of nodes in the input, hidden and output layers. with the feedback behavior, the recursive neural network can catch up with the dynamic response of the system. the recursive neural network which involves dynamic elements and feedback connections has important capabilities that are not found in feedforward networks, such as the ability to store information for later use and higher predicting precision. a recursive prediction error algorithm which converges fast is applied to training the recursive neural network. experimental results show that the performance of the recursive neural network model conforms to the sensor to be modeled, and the method is not only effective but of high precision

    根據動態校準實驗結果建立傳感器的動態數學模型，以研究傳感器的動態性能，是動態測試的一個重要內容.討論了遞歸神經網路模型在傳感器動態建模中的應用，給出了遞歸神經網路模型的結構及相應的訓練演算法.由於其反饋特徵，使得遞歸神經網路模型能獲取系統的動態響應.該方法特別適用於傳感器非線性動態建模，而且避免了傳感器模型階次的選擇的困難.試驗結果表明，應用遞歸神經網路對傳感器進行動態建模是一種行之有效的方法
  19. ( 4 ) because the speaker ’ s status is changing slowly all the time, a new online pattern updating technique is presented. after optimizing the mode of ‘ verifying after training ’ to the mode of ‘ training while verifying after training first ’, the speaker verification systems have stronger robustness. ( 5 ) programming with assembler language, a set of practical speaker verification system on spce061a is realized

    （ 4 ）針對說話人發音習慣的緩變性，提出了模板在線更新策略，把通常使用的「先訓練再識別」的更新模式，優化為在「先訓練」條件下的「邊訓練邊識別」的更新模式，從而使得說話人確認系統可適應說話人本體的特徵緩變，具有較強的適應性。
  20. Besides, it is not fit with the precise adjustment and is difficult to conform the place. a new adaptive genetic algorithm with bp algorithm to optimize weight is backed up. the algorithm which combines the merits of the global convergence of genetic algorithm with fast local researching of bp algorithm not only intensifies the gradual convergence and evolution ability but also advance the speed of convergence, precision of training and generalization

    針對傳統遺傳演算法的搜索過程帶有一定的盲目性，其收斂特性不穩定且收斂速度緩慢，特別是在系統規模較大時，優化效果的明顯改善往往需要相當長的時間，而且不適合候選解的精調，難以確定解的確切位置，提出一種新型自適應性遺傳演算法，並在此基礎上，用bp演算法優化前向神經網路權值，綜合了兩種演算法的優點，即遺傳演算法的全局收斂性和bp演算法局部搜索的快速性，強化了遺傳演算法的漸進收斂和進化能力，全面改善了演算法的收斂性，提高了收斂速度及訓練精度，也擴展了泛化能力。
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