貝葉斯解 的英文怎麼說

中文拼音 [bèiyèsījiě]
貝葉斯解 英文
bayes solution
  • 貝 : 名詞1 [動物學] （蛤螺等有殼軟體動物的統稱） cowry; cowrie; shellfis 2 （古代用貝殼做的貨幣） cowr...
  • 斯 : Ⅰ名詞（古代驅疫時用的面具） an ancient maskⅡ形容詞[書面語] （醜陋） ugly
  • 解 : 解動詞（解送） send under guard
  • 貝葉 : （印度貝多羅 pattra 樹的葉子, 古代印度人用以寫佛經） pattra leaves
  1. 3 ) we try to import the bayesian adaptation, which is widely used in speech recognition, into speaker verification. we use bayesian maximum a posteriori estimation training a speaker model from background model, to solve the problem of model miss matching in speaker verification system

    3 ）為了解決說話人確認中存在的模型不匹配問題，嘗試將語音識別中的貝葉斯自適應演算法引入到基於高斯混合統一背景模型的說話人確認系統。
  2. Cbr systems have lots of strongpoints, such as the completely expressing of the information, the incrementally learning, the precisely simulating of the visualized thought, the conveniency of the obtaining knowledge, the h igh efficiency of solving new things and so on

    Cbr的顯著優點有：信息的完全表達，增量式學習，形象思維的準確模擬，知識獲取較為容易，求解效率高等。本論文研究了貝葉斯網路、範例推理以及貝葉斯網路在範例推理中的應用。
  3. On the bayesian solutions to confirmation paradoxes

    確證悖論的貝葉斯型解決方案探析
  4. Monte carlo is a method that approximately solves mathematic or physical problems by statistical sampling theory. when comes to bayesian classification, it firstly gets the conditional probability distribution of the unlabelled classes based on the known prior probability. then, it uses some kind of sampler to get the stochastic data that satisfy the distribution as noted just before one by one

    蒙特卡羅是一種採用統計抽樣理論近似求解數學或物理問題的方法，它在用於解決貝葉斯分類時，首先根據已知的先驗概率獲得各個類標號未知類的條件概率分佈，然後利用某種抽樣器，分別得到滿足這些條件分佈的隨機數據，最後統計這些隨機數據，就可以得到各個類標號未知類的后驗概率分佈。
  5. Following this idea, considering the serious information asymmetry and personal expect utility maximization in the double auction, we intends to construct a bidding model on bayesian nash equilibrium based on incomplete information games, consequently obtain a solution on each private values and maximum forecast price and minimum forecast price on the marketing. then, we analyze in detail the characters and possibilities of the offer strategy by means of computer simulation according to the experimental economics

    在此基礎上，考慮到雙向拍賣中存在的信息嚴重不對稱和個人期望效用最大化，構造了該拍賣模式中基於不完全信息博弈的貝葉斯納什均衡模型並求解，獲得一個關于各自估價和市場最高及最低預測價格的線性函數的報價策略。
  6. In tcm this pattern is called pair of medicine, and it can be resolved by frequent pattern mining. the symptom complex diagnose can be treated as a bayesian training and a bayesian classification on large clinical database cases. the critical step to resolve the chinese prescription compounding is to build an appropriate model to express the progress of it

    中藥知識發現集中在發現常用的單味藥合用模式，在中醫術語中稱之為藥對，這可以用高頻集發現來解決；中醫癥候診斷可以看成是在大量臨床案例庫上的貝葉斯訓練器和分類器；解決方劑配伍問題的關鍵是建立起一個合適的配伍計算機模型。
  7. Cyclic bayesian network provides modeling method and inference algorithms for the management of software project iterative process risk

    有環貝葉斯網路的研究，為管理軟體項目迭代過程風險提供了建模方法和模型求解演算法。
  8. Temporal bayesian network and scheduling bayesian network provide modeling method and inference algorithms for the management of software project iterative process risk

    時間貝葉斯網路和進度貝葉斯網路的研究，為管理軟體項目時間相關風險提供了建模方法和模型求解演算法。
  9. In factual world, the uncertainty is very rich. in expert system, usually probability is defined as subjective credit degree of experts to evidence and regulation, and bayes theorem is key solution in probability reasoning

    在專家系統中，概率一般解釋為專家對證據和規則的主觀信任度，在概率推理中起著支撐作用的是貝葉斯定理。
  10. Bayesian classification is based on bayesian theorem. it can be comparable in interpretability with decision tree and in speed with neural network classifiers. bayesian classifiers have also exhibited high accuracy and speed when applied to large databases

    該演算法基於貝葉斯定理，可解釋性方面可以與判定樹相比，準確度可和神經網路分類演算法相媲美，用於大型數據庫時該演算法已表現出高準確度與高速度。
  11. Unlike other classifications, bayesian classification bases on mathematics and statistics, and its foundation is bayesian theory, which answers the posterior probability. theoretically speaking, it would be the best solution when its limitation is satisfied

    與其它分類方法不同，貝葉斯分類建立在堅實的數理統計知識基礎之上，基於求解后驗概率的貝葉斯定理，理論上講它在滿足其限定條件下是最優的。
  12. To the inequality constrained least squares adjustment problem, this paper converts many inequality constraints into one equality constraint by using aggregate function of non - linear programming ; a basic augmented lagrangean algorithm can obtain the solutions for equality constrained non - linear programming problem and the solutions are identical to those obtained by the bayesian method and / or simplex algorithm

    摘要對不等式約束最小二乘平差問題，藉助非線性規劃中的凝聚約束方法把多個不等式約束轉化為一個等式約束，採用拉格朗日極值法求解，解與貝葉斯解或單純形解一致。
  13. Classification has always been a central issue on data mining, machine learning and pattern recognition, classifier, as an important model and method of machine learning and data mining, is very important to the development and application of machine learning and the data mining. the classifier ’ s effect closely correlates with the characteristic of data sets, at present, the construction of classifier is generally based on the character of different datasets, there is no such a classifier which is suitable for any data sets. under uncertain conditions, the bayes network is a powerful tools for the knowledge expression and inference, but for difficulties in constructing its network structure and very high time complexity, it has not been considered as a classifier algorithm until the emergence of na ? ve - bayes classifier

    分類一直是數據挖掘、機器學習和模式識別等研究的核心問題，貝葉斯網路是作為知識表示和推理的強大工具，由於搜索空間巨大和學習困難的原因，直到樸素貝葉斯理論的出現才被作為分類器演算法，改進樸素貝葉斯分類器是貝葉斯分類器學習的一個主要的研究方向。遺傳演算法本質上是一種求解問題的高效并行全局搜索演算法，適合應用於那些改進的分類器的結構學習中。本文提出了一種基於遺傳演算法的ban分類器演算法。
  14. On the strength of the square loss function, this part also defines the vector loss function and matrix loss function, and discusses the bayesian risk decision solutions about random vector parameter and random matrix parameter under these loss functions respectively. secondly, the bayesian inference theory about single equation model is explored

    在單參數平方損失函數的基礎上，定義了向量損失函數，利用向量化運算元vec定義了矩陣損失函數，並討論了這兩類損失函數下隨機向量參數和隨機矩陣參數的貝葉斯風險決策解。
  15. This paper studies 3 kinds of algorithms : the viterbi algorithm, multiresolutional algorithm based on wavelet transformation and bayesian bootstrap algorithm. the viterbi algorithm is based on the hidden markov model theory and it is a kind of map estimation, this paper studies this algorithm and puts up an algorithm that suits for filtering in the presence of interference. multiresolutional algorithm takes full advantage of multiresolutional data, we can see it has a better filtering ability than the traditional filtering methods ; bootstrap algorithm is a recursive bayesian estimation, it describes the probability density function by the samples, so it can be used to nonlinear non - gaussion filtering, the simulation result of the two groundings is presented

    Viterbi演算法以隱馬爾可夫理論為基礎，是一種最大后驗概率估計方法，本文對該演算法進行了研究，給出了一種適合於非高斯干擾條件下的濾波方法；多分辨分析方法充分利用到了多解析度測量數據所包含的信息，從模擬結果中可以看出，該方法的濾波精度要高於傳統的濾波演算法；自主濾波方法是一種遞推貝葉斯估計演算法，它利用采樣點來描述目標狀態的概率密度函數，因而適用於非線性、非高斯條件下的濾波，本文分別對這兩種情況下的濾波進行了模擬。
  16. The article gives a mathematical formula theory based on kolmogorov ' s complexity, description probability, orinducing probability, and its explanation and gives a way in which mathematical representation is able to be explored

    摘要本文根據貝葉斯公式，推理概率等理論推導，討論了情報學研究中的幾個原則，並給出了相應的解釋。
  17. By introducing the two solutions, suggested by dorling and strevens respectively, to duhem ' s problem with bayesian approach, this paper aims to explain how duhem ' s problem is treated in bayesian framework, and make a comparison between the two solutions, with a conclusion that strevens ' solution is more rational and objective

    本文主要通過介紹多林與斯特雷文斯各自運用貝葉斯方法解決迪昂問題的兩個方案，試圖說明迪昂問題在貝葉斯機制中的處理方式，並且對這兩個方案作出比較，認為斯特雷文斯的方案更為客觀與合理。
  18. To build the appearance model of mouse target in video sequences, this paper studied a general method to retrieve image observation under the bayesian framework. first, the image is partitioned into numerous grids, and the image observation is assumed as independent between different grids. then the image observation of a whole image can be configured based on the configuration of image observation in each grid

    為建立視頻圖像中鼠類目標的表觀模型，本文研究了在貝葉斯框架下提取圖像觀察的一般方法，通過將圖像網格化，並認為各網格間的圖像觀察是相互獨立的，從而可以在求解各個網格圖像觀察的基礎上求解整幅圖像的表觀模型。
  19. Abstract according to the defect of the conventional bayes " method in the geomechanical engineering back analysis, expanding bayes " method was established in this paper. with the applications of the probability theory and the mathematical statistics principle, the geomechanical engineering random back analysis objects function was founded based on the aic criterion of the decision information theory and the maximum entropy criterion, a the matching question between the observed information and the previous information of the conventional bayes " method were proposed. in addition, the least square method, maximum likelihood method and conventional bayes " method were unified in form

    本文針對巖土工程反分析中使用的傳統貝葉斯法中存在的缺陷，提出了擴展貝葉斯法，從概率論和數理統計的原理出發，建立了基於決策信息論中aic準則和最大熵準則的巖土工程隨機反演的準則函數，解決了傳統貝葉斯法的觀測信息與先驗信息的匹配問題，並從形式上完成了目前常用的最小二乘法、最大似然法及傳統貝葉斯法準則函數的統一，並可由觀測數據的質量和數量進行預測模型的辨識。
  20. 10 hubel d h, wiesel t n. receptive fields, binocular interaction and functional architecture in the cat s visual cortex

    鄭南寧等人將該問題形式化為馬爾科夫網，並用貝葉斯信念傳播方法解決該問題。
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