machine training time 中文意思是什麼
machine training time
解釋
計算機訓練時間-
Hydraulic control system of double - cylinder vessel gate is a sort of typical electrohydraulic proportional control system0 in order to study electrohydraulic flux control characteristics of this system, i have analyzed the principle of this hydraulic control system, and made its mathematics model ? in double - cylinder hydraulic system, it is necessary to process electric synchronous control in this hydraulic system, this paper also introduces a sort of fnn ameliorated from the point of view of intelligent control theory, and clarifies the principle of applying that network to achieve synchronous controlo at the same time, the means of fuzzy configuration analysis is used for network training, the comparative experiments make known that the method of applying fnn to realize synchronization control is feasible, furthermore, its effect is better than others0 this paper puts forward that a distributed control system can be used to monitor and control vessel gate within a real - time or remote distance, the basic project, structure, applications and functions of computerized scada system in hydraulic system of vessel gate is introduced ? a double layer network structure, epigynous and hypogynous machine network, is applied to this system, in accord with the application of technique such as plc, integrated software etc, this paper introduces the methods and application to achieve the computerized scada system in the task, and analyzes the characteristic of this system, in this paper, the application of configuration in monitor and control system of vessel gate is discussedo in addition, in accord with the application of technique such as visual basicb
雙缸船閘液壓啟閉控制系統要求解決同步控制問題，文中從智能控制理論角度出發，採用了一種改進的模糊神經網路，結合模糊聚類分析方法，闡述了應用該網路實現同步控制的原理。通過對比模擬實驗表明：應用模糊補經網路實現同步控制是可行的，而且它的同步控制效果要優于傳統的設置主從令缸控制方法，具有良好的魯棒性能。另外，本文提出了建立船閘控制系統的分散式控制系統，介紹了船閘液壓控制系統的計算機監控系統（ scada ）的方案、結構、應用和主要功能，採用雙層網路化結構：上位機網路和下位機網路，並結合plc通信網路技術和組態軟體等技術構成的計算機監控系統的實現方法，實際應用，分析了這種較新的系統模式在船閘液壓控制系統的計算機監控系統的功能實現中所具有的特點。 -
Full - time and part - time courses offered by the skills centres include general service work, office assistant practices, commercial and retailing service, basic catering service, interior decoration, office computing and practice, machine sewing, printing, packaging service and logistics service, etc. all these training programmes are designed to meet industry needs and the aspiration of the trainees
技能訓練中心提供多個全日制及夜間課程，包括：辦公室實務、商業及零售、基本飲食實務、室內裝修、電腦運用及商業實務、工業車縫、印刷、包裝服務和物流服務等。所有課程均是配合勞動市場和學員的需要而編訂的。 -
Within the framework of sparse bayesian learning, the algorithm extends the relevance vector machine by combining global and local kernels adaptively in the form of multiple kernels, and the improved locality preserving projection ( llp ) is then applied to reduce the column dimension of the multiple kernel input matrix to achieve less training time
在稀疏貝葉斯學習的框架下，該演算法首先以多核形式自適應結合全局核函數和局部核函數擴展相關向量機，然後應用改進的保局投影來約簡多核輸入矩陣的列維數以減少訓練時間。 -
Experiments with real images indicate that the proposed algorithm performs better than the support vector machine and the relevance vector machine while requiring less training time than the relevance vector machine
基於真實圖像的實驗表明所提演算法優于支持向量機和相關向量機且其訓練時間小於相關向量機。 -
The bic method generalized from ar model was adopted to determine the number of input neurons in grnn prediction model. the grnn was applied to single - step and multi - step ahead prediction of the vibration time series of a rotating machine, and its performance was compared with that of 3 - layers perceptrons network with error back propagation training algorithm ( bpnn ). it is indicated that the grnn is more appropriate for prediction of time series than the bpnn, and the performance of grnn is qualified even with sparse sample data
研究了基於廣義回歸神經網路（ grnn ）的大型旋轉機械振動狀態預測，提出了應用bic準則確定grnn預測模型輸入神經元數目的方法，將grnn用於大型機組振動峰?峰值時間序列的預測，與採用誤差反向傳播學習演算法的三層前饋感知器網路（ bpnn ）的預測結果對比表明， grnn的預測性能優于bpnn ，而且，即使樣本數據稀少，也能獲得滿意的預測結果。
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