learning algorithm 中文意思是什麼
learning algorithm
解釋
演演算法-
Support vector aam based iterative learning algorithm for gender classification
迭代學習的性別分類演算法 -
This paper adopts an adaptive learning algorithm based on hierarchy clustering to update user profile, which continuously abstract the cancroids of one class of optimum information from the feedback flow of system, which effectively shield the learning process from plenty of feedback noises produced by distorted threshold and sparseness of initial information, which also can imitate artificial feedback approximately to perfect the intelligence of adaptive learning mechanism
摘要本文採用一種基於層次聚類的自適應學習策略，從系統反饋的信息流中，動態提取一類最優信息的質心更新用戶模型，有效屏蔽了閾值失真和初始信息稀疏造成的大量反饋噪聲，並且能夠近似模仿人工反饋，完善自適應學習機制的智能性。 -
The algorithm speeds up network study train, compared with the real - time recurrent learning algorithm consumedly, and increases the accuracy of prediction
與已有的實時循環學習演算法相比，極大的提高了網路學習訓練的速度，並且提高了預測的精度。 -
A new learning algorithm of the continue wavelet networks parameters is proposed, that is, hybrid parameters learning algorithm. the parameters of wavelet networks are divided into two parts, and different methods are used to training them. compare to the traditional parameters learning method, the new method proposed in this paper has the advantages of rapid convergence speed and high approximation capability
提出了連續小波網路的混和參數訓練方法，將小波網路參數分為小波系數和網路權值兩部分，對這兩部分參數分別採用不同的方法進行訓練，這一新的訓練方法相對于傳統的小波網路參數訓練方法來說具有收斂速度快，逼近精度高等優點。 -
A subsection learning algorithm based on
基於支持向量機的分段線性學習方法 -
A novel learning algorithm for synergetic pattern recognition
一種新的協同模式識別學習演算法 -
To achieve this goal, this paper design a neural network with three layers in which the first layer play a classifier role and learn with the memory - based learning algorithm while the second and third layers learn with the error back - propagation algorithm
根據這一需要，本文建立了三層神經網路，第一層起分類作用，採用基於記憶學習演算法，第二、三層採用誤差反饋學習演算法。 -
While network - based intrusion detection systems usually detect packet headers or part of those headers, this system examines the packet payload as well as headers. not only the attributes are detected respectively, but also the relationships of attributes occurrence are detected according to a set of conditional rules, which is generated automatically by a machine learning algorithm
常見的基於網路的入侵檢測系統一般只對網路數據包的包頭或包頭中的某些內容進行考察，而本文實現的原型系統不僅考察數據包的包頭，而且還考察數據包應用負載的部分內容。 -
Simulation results show that both of them have satisfactory performance and strong robustness. 2. to ph processes, which are nonlinear and time varying, the neural network model is structured and the learning algorithm is presented, based on which the model - free controller is designed, while the controller gain is scheduled by a fuzzy method
針對具有嚴重非線性和不確定性的ph中和過程，給出一種神經網路模型，提出了一種神經非模型控制方法，該方法利用模糊演算法在線調整神經網路控制器的增益，模擬實驗表明這種基於神經網路的非模型控制方法能有效控制ph過程，具有優良的控製品質和強魯棒性。 -
Neural network control is an important mode of intelligent control, and it is widely used in branches of control science, first, the architecture and the learning rule ( error back propagation algorithm ) of multiplayered neural network which is widely used in control system are presentedo especially, the paper refers to the architecture of diagonal recurrent neural network and its learning algorithm - - - - - recurrent prediction error algorithm because of its faster convergence with low computing costo next, before introducing the neural network control to the double close loop dc driver system, the controllers of current and velocity loop are designed using engineering design approach after analysis of the system, simulation models of the system are created
神經網路控制是智能控制的重要方式之一，它廣泛應用於自動控制學科各個領域。本文首先敘述了控制系統中常用的多層前饋網路結構及演算法（ bp演算法） ，特別提及了能夠較好描述系統動態性能的對角遞歸神經網路和在用遞推預報誤差演算法訓練drnn時取得了較快的收斂速度。其次，應用工程方法分析設計了tf - 1350糖分離機的電流、轉速雙閉環直流調速系統的控制器，作為引入神經網路控制的設計基礎，並建立了系統的模擬模型。 -
To overcome the limitations of general fnns and bp algorithm, this thesis introduced a hybrid feed - forward neural network, which is composed of a linear model and a general multi - layer fnn, and proposed a new learning algorithm for the hybrid fnn
其次，針對bp網路存在的缺陷，結合前向神經網路和線性最小二乘法的優點，構造了一種基於混合結構的神經網路，提出了相應的非迭代的快速學習演算法。 -
A double - bagging machine - learning algorithm was used to train classification rules on the basis of a combination of fdt scores and nerve fiber related visual field losses in swap
在聯合fdt評分和swap神經纖維相關的視野缺損基礎上用雙相機器學習系統排列分類法則。 -
Moreover, this article also made a preliminary discussion on the combination of neural network theory and the differential game guidance law. the bp model and rbf model and their corresponding learning algorithm were employed to design the neural network guiding rule based on the differential game guidance law
另外，本文還將神經網路理論與微分對策制導律相結合作了初步的探討，並結合具體的bp網路和rbf網路及其相應的學習演算法設計出了基於神經網路技術的微分對策制導律。 -
Due to these basic problems and also because of the need to include information on specific domain, this paper proposes an efficient strategy of studying user ' s interests, which is based on temporal difference method, a re _ inforcement learning algorithm, and vector representation
由於這些基本問題以及對特定領域的信息學習的需要，本文以強化學習的時間差分法和向量表示為基礎，提出了一種高效的學習用戶興趣的策略，並設計了一個學習用戶興趣的用戶界面。 -
Based on the discussions of the conventional and recent methods of short term load forecasting such as time series, multiple regression approaches and artificial intelligence technologies, this paper presents a hybrid short term forecasting model which combines the artificial neural network ( ann ) and genetic algorithm ( ga ). in order to improve the convergence speed and precision of the back - propagation ( bp ), a new improved algorithm - the adapted learning algorithm based on quasi - newton method is given
本文首先分析比較了電力系統短期負荷預測的傳統方法時間序列法和回歸方法以及最近的專家系統和神經網路技術的優點和不足，然後針對人工神經網路bp演算法的不足對其進行了改進，採用了基於擬牛頓的自適應演算法，它提高了網路學習效率，具有較快的收斂速度和較高的精度。接著提出了改進的遺傳演算法來改善神經網路的局部收斂性。 -
And it is obvious that pseudo - relaxation is a kind of local optimization method, so it cannot guarantee to get the global optimal solution. in this paper, a novel learning algorithm eprbam evolutionary psendo - relaxation learning algorithm for bidirectional association memory employing genetic algorithm and pseudo - relaxation method is proposed to get feasible solution of bam weight matrix
即使在和取定后，準鬆弛演算法的訓練和學習仍是一種局部最優化過程，它只是在初始權矩陣的附近找到第一個可行解就結束訓練，這類演算法並不能保證獲得全局最優解。 -
In the final, the thesis build a rapid face detection system using a cascaded classifiers based on adaboost learning algorithm, harr - like feature and the method of building classifier
最後本文運用基於adaboost學習演算法和harr - like特徵及本文提出的由特徵構造分類器方法，採用一種分級分類器的結構，搭建了一個快速的人臉檢測系統。 -
There are three factors must research in the rapid face detection method based on learning : learning algorithm, the definition of features and the method of building classifier based on these features, the manner of combining effectively these features
本文認為，在基於學習的快速人臉檢測方法中，有三個需要研究的要素，分別是學習演算法、特徵的定義及基於此特徵形式構造分類器的方法和特徵的有效組合方式。 -
L3ased on the organization rules of internet data, the distribution laws of hyperlinks and the name rules of url, a algorithm of tvm rebuilding is established, and satisfactory experiment results are obtained by applying this algorithm. furthermore, efforts are made by applying of tvm on browse navigation, web page classification and reinforcement learning algorithm
結合網際網路資源的構建規則、鏈接分佈規律和url命名規則，論文提出了樹藤共生數據模型的重建演算法，實驗結果驗證了樹藤共生模型的有效性與合理性，在此基礎上初步討論了樹藤共生模型在瀏覽導航、網頁分類和reinforcementlearning演算法中的應用。 -
A neural network learning algorithm based on fuzzy deduction
一種基於模糊推理的神經網路學習演算法
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