rbf radial basis function 中文意思是什麼
rbf radial basis function
解釋
徑向基函數-
Finally radial basis function ( rbf ) is adopted to identify the moment coefficient
最後還採用徑向基函數神經網路識別了力矩系數。 -
In macroscopic aspect, it is taken as an example about how to model the relationship between the mix proportion of raw materials and the compressive strength of concrete using radial basis function ( rbf ) neural networks, which can achieve a global minimum
宏觀上，以混凝土強度為例，研究如何利用神經網路建立原材料配方與混凝土強度的關系模型。介紹可以全局收斂的徑向基函數（ radialbasisfunction ， rbf ）神經網路。 -
Icbp is a generalization to circular back - propagation ( cbp ) network. cbp possesses good generalization ability and adaptability compared with the counterpart bp. and in its frame we can construct vector quantification ( vq ) and radial basis function ( rbf ) networks, showing great flexibility
Icbp是我們對圓形反向傳播網路（ circularbackpropagation ? cbp ）的推廣， cbp不僅具有良好的推廣和自適應能力，而且在其框架下分別構建出矢量量化（ vq ）和rbf網路，展示出了極大的靈活性。 -
Based on visual rice growth models ( vrgm ) and with rice tillering as examples, the back - propagation artificial neural networks ( bp ) and radial basis function networks ( rbf ) were established to simulate the rice growth and to compare with statistical model and dynamic model
3 、在研製可視水稻生長模型的基礎上，進一步利用人工神經網路bp模型和rbf模型，對水稻生長進行了模擬與模擬。並以水稻群體莖蘗動態為例，與水稻群體分蘗的統計模型和動力學模型進行了比較。 -
The flood and drought in both first stage and second stage of rainy season in fujian province were forecasted by the ways of line regression prediction equation and three kinds of artificial neural network models, the results show : the backpropagation ( bp ), radial basis function ( rbf ) and elman neural network models are much better than line regression prediction equation in historical sample fittings, independent sample test, actual prediction ability
（ 3 ）運用線性回歸預報方程和三種人工神經網路模型對福建汛期旱澇進行預測的實驗表明： bp 、徑向基（ rbf ）和elman這三種人工神經網路模型在歷史樣本擬合精度上、獨立樣本檢驗結果和網路模型的實際預測能力上都明顯優于傳統的線性回歸方法。 -
Through study of correlative contents of advanced computer cybernetics, artificial intelligence, the domain knowledge and special crop growth mechanism in greenhouse, we present the system of multi - sensor data fusion ( msdf ) based on radial basis function network ( rbf ) to implement on line detection for nutrient - liquid, which may realize multiple components detection on - line, for example no3 -, cl -, ca2 +, ph, ec, nh4 +, k + and so on. the soft sensor ' s mechanism is introduced to overcome the limitations of sensor ' s manufacturing process. to improve the believe - degree of soft sensor ' s result, we analyze soft sensor ' s result by uncertain inferential capacity and combination rule of evidential theory
本論文通過對計算機技術、控制理論、人工智慧技術和設施農業領域知識等相關理論的研究，結合對特定溫室蔬菜生長的研究與機理分析，提出了一種基於rbf神經網路的營養液多傳感器數據融合（ msdf ）系統，實現對營養液組分： no _ 3 ~ - 、 cl ~ - 、 ca ~ （ 2 + ） 、 ph 、 ec 、 nh _ 4 ~ +和k ~ +的在線檢測；對于由於目前傳感器製造工藝的限制而不能在線檢測的離子成分如磷酸根和硫酸根，提出了一種基於徑向基函數網路的軟測量機制，可以有效地實現對營養液中磷酸根和硫酸根成分的實時檢測；為了提高軟測量結果的可信度，利用d - s證據理論的不確定推理能力和合成公式，結合領域知識對軟測量結果進行可信度分析。 -
Also the thesis improves the diagnosis model of fuzzy neural networks, and establishes the composite sub - nets based on rbf ( radial basis function )
通過改進模糊神經網路診斷模型，建立rbf徑向基函數組合子網路診斷系統，增強對故障分類的能力。 -
( 1 ) in view of practice that the data obtained from accelerometer has serious zero deviation, it is very difficult to diagnosis fault by hardware redundant. a fault diagnosis scheme for multi - accelerometers employing predictor based on radial basis function ( rbf ) neural network is proposed
論文的主要創新成果有： （ 1 ）在擺式列車實際運行中，檢測子系統的加速度傳感器存在嚴重零偏，使用硬體冗餘法進行故障診斷的設計初衷面臨著巨大的困難。 -
An identification algorithm for vibrating dynamic characterization by using rbf ( radial basis function ) artificial neural network is developed for multi - degree of freedom systems
基於徑向基函數（ rbf ）神經網路，提出了水輪機振動荷載參數識別方法。 -
After that, the optimal proportional strategy of group of aircrafts is studied by the method of mixed strategy and the fuzzy theory in order to gain optimal consequence of air - combat. lastly, the optimized proportional navigation of modern fighter is researched with radial basis function ( rbf )
根據混合策略理論與模糊理論，應用模糊最優混合策略的方法，依取得最優策略值（即最佳空戰效果）為目的，對參戰機群按最優策略求取最佳分配比例關系，實現機群按比例優化配置。 -
An improved clustering method is provided which is based on radial basis function neural network, and applied rbf neural network into the speech sounds recognition domain, and a speaker - independent isolated words speech recognition system is established
摘要提出一種基於徑向基函數神經網路的改進聚類方法，並將此改進的神經網路應用於語音識別領域，建立一個非特定人的孤立詞語音識別系統。 -
This method combines a genetic algorithm with an artificial neural network classifier, such as back - propagation ( bp ) neural classifier, radial basis function ( rbf ) classifier or learning vector quantization ( lvq ) classifier
此方法結合基因演演算法與類神經分類器，如倒傳遞分類器、放射基底函數分類器以及學習矢量量化分類器。 -
Radial basis function, rbf
本文採用徑向基函數 -
In view of chaotic systems composed of a sum of a linear and nonlinear part, a compensative control method using radial basis function networks is proposed, the rbf networks trained can eliminate the nonlinear part of the chaotic system, the resulting system is dominated by the linear part
然後針對大多數混沌非線性系統由線性函數和非線性函數兩部分構成的特點，用rbf網路補償系統非線性部分，使原系統變成近似線性系統，再結合線性狀態反饋控制技術，對lorenz方程和duffing振子進行了非線性補償控制。 -
A self - adapting fault diagnosis method based on radial basis function ( rbf ) networks is studied in the thesis
研究了基於自適應徑向基函數（ rbf ）網路的故障診斷方法。 -
The quasi - steady state model of temperature profile for the reverse flow reactor with catalytic combustion of air contaminated with volatile organic compounds ( vocs ), is developed by rbf ( radial basis function ) neural networks
摘要用rbf神經網路建立了用於清除低濃度揮發性有機物的流向變換催化燃燒反應器擬定態溫度分佈模型。 -
A new method of determining the characteristics of low - loading strengthening for automotive structural parts is presented based on radial basis function ( rbf ) neural network
摘要提出了一種基於徑向基函數神經網路的汽車結構件低載強化特性確定方法。 -
However, there have still some unresolved problems : first, how to determine the number and size of the clusters automatically during the clustering process. second, how to utilize the " local " ridge regression method which including multiple regularization parameters in learning rbf network. third, those clusters in irregular form ca n ' t represented by radial basis function, thus we must find some other basis functions that can describe the irregular form
但是仍然存在幾個問題尚待解決：首先，聚類時怎樣自動確定簇的個數和半徑；其次，如何利用含有多個正規化參數的局部嶺回歸方法進行rbf網路學習；第三，如果簇的形狀是不規則的，則它很難用徑向基函數來描述，因此需要研究其它能代表不規則形狀的簇的基函數。 -
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訓練，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懲罰項，從而保證網路輸出函數具有一定的平滑度。
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