probabilistic network 中文意思是什麼

probabilistic network 解釋
概率網路
  • probabilistic : adj. 1. （天主教教義）蓋然論的，或然說的。2. 概率的，幾率的。
  • network : n. 1. 網眼織物。2. （鐵路、河道等的）網狀系統，網狀組織，廣播網，電視網，廣播[電視]聯播公司。3. 【無線電】網路，電路。4. 【計算機】電腦網路，網。
  1. Among the probabilistic approaches, pearl ' s belief network is the most representative, due to its rigorousness and consistence in theory, the efficient local computation mechanism and intuitive graphical expression of knowledge

    在概率方法中，信度網由於其理論的健壯性和一致性、有效的局部計算機制和直觀的圖形化知識表達方式而日益受到重視。
  2. Structural damage localization using probabilistic neural network

    用概率神經網路進行結構損傷位置識別
  3. 2 a radio broadcast network ( rbn ) is modeled by a probabilistic graph g with unreliable nodes and perfect edges

    2無線廣播網路（簡稱rbn ）可以用一個點不可靠而邊可靠的概率圖g來表示。
  4. Improving the recognition rate of eeg in bci based on genetic algorithm and probabilistic neural network

    基於遺傳演算法和概率神經網路提高腦機介面中腦電信號識別率
  5. Resource leveling optimization of network scheduling under probabilistic time and cost

    上升線性需求條件下考慮資金時間價值的變質性物品生產庫存模型
  6. In 1991, he introduced the concept of soft computing, the principal constituents of which are fuzzy logic, neural network theory and probabilistic reasoning

    一九九一年澤德教授提出軟計算的概念，內容主要包括快思邏輯、神經網路理論及概率推理。
  7. ( 5 ) a series of design methods of classifiers are proposed, including the classifier based on the generalized inverse and the probabilistic reasoning method ( prm ), a new self - adaptive kohonen clustering network which overcomes the shortcomings of the conventional clustering algorithms, and the fuzzy neural classifier. the experimental study efface recognition is presented based on the combination of multi - feature multi - classifier. ( 6 ) this paper proposes a hybrid feature extraction method for face recognition, which is a combination of the eigen matrix, fisher discriminant analysis, and the generalized optimal set of discriminant vectors

    （ 5 ）對圖象分類器設計方法進行研究，主要包括：提出了一種基於廣義逆和概率推理的分類器設計方法；提出了一種新的自適應模糊聚類演算法；提出了基於模糊神經網路的分類器設計方法；並對多特徵多分類器組合方法在人臉識別中進行實驗研究； （ 6 ）提出了一種只要一個訓練樣本就能解決人臉識別問題的新方法，該方法結合了特徵矩陣、 fisher最優鑒別分析和廣義最優鑒別分析方法的優點。
  8. Structural damage detection based on adaptive probabilistic neural network

    自適應概率神經網路結構損傷檢測
  9. Fuzzy probabilistic neural network water quality evaluation model and its application

    模糊概率神經網路水質評價模型及其應用
  10. Application of probabilistic neural network in text - independent speaker identification

    概率神經網路在文本無關說話人識別中的應用
  11. Radial basis function based probabilistic neural network in arrhythmia classification

    基於徑向基函數概率神經網路的心律失常自動識別
  12. Delineation of coastal region of south china - with matlab to create radial basis probabilistic neural network

    華南沿海潛在震源區劃分運用matlab徑向基概率神經網路工具箱求解
  13. The main factors of probabilistic neural network including the hidden neuron size, hidden central vector and the smoothing parameter, to influence the pnn classification, are analyzed ; the xor problem is implemented by using pnn. a new supervised learning algorithm for the pnn is developed : the learning vector quantization is employed to group training samples and the genetic algorithms ( ga ’ s ) is used for training the network ’ s smoothing parameters and hidden central vector for determining hidden neurons. simulations results show that, the advantage of our method in the classification accuracy is over other unsupervised learning algorithms for pnn

    本文主要分析了pnn隱層神經元個數，隱中心矢量，平滑參數等要素對網路分類效果的影響，並用pnn實現了異或邏輯問題;提出了一種新的pnn有監督學習演算法:用學習矢量量化對各類訓練樣本進行聚類，對平滑參數和距離各類模式中心最近的聚類點構造區域，並採用遺傳演算法在構造的區域內訓練網路，實驗表明:該演算法在分類效果上優于其它pnn學習演算法
  14. Two spatially registered images with different focuses are decomposed into several blocks. then, three features reflecting the clear level of every block, i. e., spatial frequency, visibility, and edge, are calculated. finally, artificial neural networks, i. e., multilayer - perceptron, radial - basis function, probabilistic neural network, are used to recognize the clear level of the corresponding blocks to decide which blocks should be used to construct the fusion result

    具體實現過程概述如下：首先將兩幅（或多幅）配準圖象進行分塊處理，提取兩幅圖象中對應塊的能反映圖象清晰度的三種特徵，即空間頻率、可見度和邊緣，將特徵歸一化後送入訓練好的神經網路進行識別，根據得到的結果依據「誰清晰誰保留」的原則構成融合的圖象。
  15. In this dissertation, several technology problems of pulse trains deintrleaving algorithms are dealt with, they are presorting techniques based on coherent processor, probabilistic neural network deinterleavers, adaptive data association methods for pulse trains analysis and deinterleaving, signal processor designing issues. the research is focused on real time processing. the coherent processor is a crucial technique for real time presorting

    本論文研究高密度復雜信號下的脈沖列去交錯技術的若干問題，包括基於關聯比較器的信號預分選技術研究；概率神經網路脈沖去交錯器的研究與設計；卡爾曼濾波和概率數據關聯方法用於脈沖列分析和去交錯；雷達截獲系統信號處理器設計等等。
  16. The probabilistic approaches include the belief network, the dynamic causality diagram, the markov network, the approach used in prospector, etc. the non - probabilistic approaches include the certainty factor theory in mycin, fuzzy set logic, dempster - shafer theory, etc. the non - probabilistic approaches have reached some achievement in their respective application domain, and shown their shortage while applying

    另一類是非概率的方法，包括mycin的可信度因子（ certaintyfactor ） 、模糊邏輯（ fuzzylogic ）以及dempster - shafer的證據理論等。非概率的方法雖然在各自的應用領域都取得了一定成果，但在運用過程中人們越來越意識到這類方法的不足。
  17. Bn is network structure with clarity semantics. lt exploits the structure of the domain to allow a compact representation of complex joint probability distribution. its sound probabilistic semantics, explicit encoding of relevance relationships, inference algorithms and learning algorithms that are fairly efficient and effective in pratice, and decision - making mechanism of facility, have led bn to enter the artificial intelligence ( ai ) mainstream. for the reasons that they have produced more and more practical values and economic profits in many important application fields, such as modern expert systems, diagnosis engines, decision support systems, and data mining systems, researchers from both industry and academia are thus taking them much seriously

    它具有清晰語義的網路結構；它揭示領域對象的內在結構，是復雜全概率分佈的緊湊表示方式；其堅實的理論基礎、知識結構的自然表述方式、靈活的推理能力、方便的決策機制及有效的學習能力使其成為一種主要的不確定知識的處理方法。貝葉斯網路已經在專家系統、決策支持系統、數據挖掘系統和範例推理系統等許多重要領域產生應用價值和經濟效益。
  18. Probabilistic neural network ( pnn ) is a classification network, which is based on bayesian decision theory and probability function estimation theory

    D . f . specht提出的概率神經網路（ probabilisticneuralnetwork ， pnn ）是基於密度函數估計和貝葉斯決策理論而建立的一種分類網路
  19. A temporal reasoning method based on probabilistic temporal network in situation assessment

    態勢估計中一種基於概率時間網路的時間推理方法
  20. These coherent processors can fulfill arbitrary complex parameters. chapter 4 puts forward two deinterleaving methods based on probabilistic neural network ( pnn ). the self - organization pnn deinterleaver is suitable for unknown emitters, while the rbpnn deinterleaver is suitable for known emitters

    神經網路用於脈沖列去交錯是國內外一直關注的解決方案，論文第四章討論了基於概率的分類原理，提出了兩種概率神經網路脈沖去交錯器結構，分別適用於未知輻射源及具有先驗信息輻射源兩種情況。
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