練習線路 的英文怎麼說
中文拼音 [liànxíxiànlù]
練習線路
英文
drill circuit- 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...
- 線 : 名詞1 (用絲、棉、金屬等製成的細長的東西) thread; string; wire 2 [數學] (一個點任意移動所構成的...
- 路 : 1 (道路) road; way; path 2 (路程) journey; distance 3 (途徑; 門路) way; means 4 (條理) se...
- 練習 : 1. (反復學習) practise; practice 2. (習題或作業等) exercise
- 線路 : 1. [電學] circuit; line 2. [交通運輸] line; route
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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。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。Thirdly, the necessary skills in the process of crm training and the method how to evaluate the crm skills are researched. finally, an e - learning system about crm using the advantages of web is designed in order to provider technical services in accordance with the concept level of crm training
三、對機組資源管理技能訓練以及技能評估方法進行研究,設計了機組資源管理技能評估表,同時利用網際網路技術的優勢,初步設計開發了機組資源管理在線學習系統的構架,為實施機組資源管理的概念訓練提供幫助。The difference is that unlike the leaf, the rider can control the path that he wants to go to
和落葉不同的是,練習者可以控制他想走的路線。Neural networks are used more frequently in lossy data coding than in general lossless data coding, because standard neural networks must be trained off - line and they are too slow to be practical. in this thesis, statistical language model based on maximum entropy and neural networks are discussed particularly. then, an arithmetic coding algorithm based on maximum entropy and neural networks are proposed in this thesis
傳統的人工神經網路數據編碼演算法需要離線訓練且編碼速度慢,因此通常多用於專用有損編碼領域如聲音、圖像編碼等,在無損數據編碼領域應用較少,針對這種現狀,本文詳細地研究了最大熵統計語言模型和神經網路演算法各自的特點,在此基礎上提出了一種基於神經網路和最大熵原理的算術編碼方法,這是一種自適應的可在線學習的演算法,並具有精簡的網路結構。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。Judging by simulation experiments, the approach can accurately on - line detect sensor fault, separate the fault sensors in the meantime, and it can provide system and equipment with temporary predictive signals
該方法採用在線學習訓練網路,並給出傳感器的預測信號,對傳感器是否發生故障做出檢測,模擬實驗證明,該方法對傳感器的故障能在線做出準確的檢測,同時隔離故障傳感器並為系統和設備提供臨時的預測信號。Engineering drawing has always been labeled as a practical subject. a combination of geometrical, building. mechanical and electrical drawing, it relates between theory and the picture of reality. engineering drawing will provide an accurate and complete ptcture for every object tn terms of shapes and sizes. usually, it is taught using the face - to - face teaching mode even in an odl environment. due to its nature, some students may find difficulty in imagining and interpreting the drawings. however, the availability of sophisticated technology provides the opportunity for the learning of engineering drawing to be enhanced via online. a web - based system for teaching and learning engineering drawing was developed based on a constructivism model. the web - based system is tailored for several topics of engineering drawing such as orthographic projection, sectional view, isometric and oblique drawing at the secondary level. the learning strategy consists of multiple phases beginning with introduction, concept learning, engineering drawing method, application and exercises. during introduction, students will be exposed to an overview of the topic followed by learning of specific concepts. the system provides a learning environment that allows engineering students to view objects from different angles, such as third angle projection and first angle projection as well as views of plans, side and front elevations. after learning about the concepts, students wilt be guided through the various steps in drawing methods for each topic via animations and simulations. learners are able to view any section repeatedly. examples of real application of engineering drawings were also given using graphic, animations and video. to evaluate students understanding, exercises were given at the end of each session
工程制圖一直被認為是一門實踐性學科,其整合了幾何學、建築、力學、電子制圖等,從而將理論與現實圖像聯系起來,工程制圖能為每個不同形狀、尺寸的物體提供精確的、完整的圖像.通常,即使在開放與遠程教育環境中,工程制圖的教學也是通過面對面的教學模式來進行的.由於其特殊性,一些學習者可能難以想象並解釋這些圖像.然而,尖端的技術使得可以通過在線的方式加強工程制圖的學習.研究者基於建構主義模式開發了一個面向工程制圖教學和學習的網路系統.該系統適用於幾種工程制圖,例如展開圖、刻面圖、等角圖和斜角圖.學習過程包括導論、概念學習、工程制圖方法,以及應用與練習等階段.在導論階段,系統為學習者提供了專題簡介,然後是概念學習階段.系統所提供的學習環境允許工程專業的學生從三維透視、一維透視、平面圖、側立面、正立面等不同角度來觀察物體.經過概念學習階段后,系統將引導學生通過動畫和模擬學習每個專題中制圖方法的不同步驟,學習者也能重復觀察任何剖面.另外,還通過圖像、動畫和視頻等方式展示真實的工程制圖應用案例.最後,為了評價學生的理解能力,在每部分內容後面都附有相關的練習It is equipped with campus wireless network, computer rooms, language laboratories, a library, lecture theatres and a wide range of workshops, laboratories, fashion design studios and special rooms. in addition, there are sports facilities such as a multi - purpose hall, cafeteria, a roof - top tennis court, a basketball court and a physical fitness room
設有校園無線網路、電腦室、語言練習室、圖書館、演講廳、各類工場、實驗室、時裝設計室、特別活動室、多用途禮堂、自助食堂、天臺網球場、籃球場及健身室等。Fnn efficiently maps the complex non - linear relationship of training data for its automatic learning, generation and fuzzy logic inference
模糊神經網路具有很強的自學習、泛化和模糊邏輯推理功能,可以有效地映射出訓練數據之間復雜的非線性關系。According to the requirements to pd pattern auto - recognition, this paper studies systematically the basic theories and realizable methods for auto - recognition of pd gray intensity image : ( 1 ) in the requirement of on - line pd monitoring for transformer, several discharge models are designed and the relevant experiment methods projected. with discharge model tests, a lot of discharge sample data is acquired. on the base of systematical research on recognition for pd gray intensity image, this paper puts forward two kinds of fractal features, the 2nd generalized dimensions of original pd images and fractal dimensions of high gray intensity pd images, and then the relevant extraction methods
針對局部放電模式自動識別的需要,作者系統地研究了局部放電灰度圖像自動識別中的基本理論和實現方法: ( 1 )根據變壓器局部放電在線監測的要求,設計了放電模型和實驗方法,並通過模型實驗獲得了大量放電樣本數據,為構造局部放電灰度圖像和採用bpnn進行識別作好準備; ( 2 )研究了局部放電灰度圖像的構造方法以及降維構造32 32灰度和矩陣的方法;在用人工神經網路對局部放電進行模式識別時,分析了bp網路的優缺點,對典型bp網路的結構和學習訓練演算法提出了改進,採用帶有偏差單元的遞歸神經網路作為模式分類器;採用32 32灰度和矩陣進行bpnn識別結果表明這種方法是有效的。The radio detection trainer can use the following three training methods as single. machine training mode, network training mode and radio detection knowledge to perform radio detection individual soldier training, radio detection network military exercises and radio detection knowledge learning
無線電監測人員可採用單機模式下技偵業務訓練虛擬現實、網路模式下技偵業務訓練虛擬現實和無線電監測知識等三種訓練方法,分別進行無線電監測單兵訓練、無線電監測網上演習和無線電監測知識的學習。Attention : in order to have good performance during mock test, we strongly suggest to avoid using internet at rush hour. in additional, broadband " bandwidth " network is always recommanded
另外,因為網路頻寬的問題,建議考生盡量使用寬頻網路,千萬不要使用撥接網路,且不要在網路擁擠的時間上線練習,可以讓模擬練習的品質更好喔~Artificial neural networks have mighty learning ability. after being properly trained, the multiplayer networks are capable of approximating any nonlinear functions with any precision. therefore it has become a powerful tool in nonlinear system identification field
人工神經網路具有很強的學習能力,經過訓練的多層神經網路能以任意精度逼近非線性函數,因此為非線性系統辨識提供了一個強有力的工具。Jackson wanted bynum to keep working on his post moves, and he also drew the distinction between bynum fighting for his own baskets as opposed to connecting on easy dunks off well - placed lobs from teammates
禪師希望他可以繼續努力練習禁區內腳步移動,同時也提了一個差別:拜納姆在爭取自己的投籃機會的路線和接收隊友傳球后輕松灌籃是不一樣的。An artificial neural network ( ann ) model was developed and used in different water bodies to predict timing for environmental changes as well as for the dynamics of resources. the results show that the ann model is superior to classical statistical models ( csm ) and can be used as predictive tool for highly non - linear phenomena
用人工神經網路方法對不同水域、不同環境因子之間非線性和不確定性的復雜關系進行學習訓練並預測檢驗,結果表明:人工神經網路方法在模擬和預測方面均優于傳統的統計回歸模型,在資源與環境方面的應用是可行的,具有較強的模擬預測能力。He hit every practice shot to a target with a committed ball flight
他擊打每一個練習球按照期望的飛行路線去到目標。Andrew bynum : running track. hitting the weights. that ' s pretty much it. basketball stuff, i did with him and gerald wilkins
按路線跑動,減肥,大概就這些。籃球組里,我和他和傑拉爾德一起練習。Radial basis function neural network ( rbfnn ) is chosen to build predictive model. rbfnn is a special type of neural network linear - in - weight in nature and having nonlinear processing properties. finally, an adaptive filter is applicable to do the followed weak signal extraction work
接著選用徑向基函數神經網路( radialbasisneuralnetwork , rbfnn )建立混沌時間序列預測模型,徑向基函數神經網路是一種局部逼近的人工神經網路,訓練簡潔而且學習收斂速度快,能夠逼近任意非線性函數,最後將預測誤差送入自適應信號分離器進行處理,檢測出微弱信號。2. on the base of detailedly analysing the fourier neural networks, we find this neural networks have the characteristic which can transform the nonlinear mapping into linear mapping. so, we improve the original learning algorithm based on nonlinear optimization and propose a novel learning algorithm based on linear optimization ( this dissertation adopts the least squares method ). the novel learning algorithm highly improve convergence speed and avoid local minima problem. because of adopting the least squares method, when the training output samples were affected by white noise, this algorithm have good denoising function
在詳細分析已有的傅立葉神經網路的基礎上,發現傅立葉神經網路具有將非線性映射轉化成線性映射的特點,基於這個特點,對該神經網路原有的基於非線性優化的學習演算法進行了改進,提出了基於線性優化方法(本文採用最小二乘法)的學習演算法,大大提高了神經網路的收斂速度並避免了局部極小問題;由於採用了最小二乘方法,當用來訓練傅立葉神經網路的訓練輸出樣本受白噪聲影響時,本學習演算法具有良好的降低噪聲影響的功能。分享友人