貝葉斯概率 的英文怎麼說

中文拼音 [bèiyèsīgàilǜ]
貝葉斯概率 英文
bayesian probability
  • 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
  • 概 : Ⅰ名詞1 （大略） general outline 2 （神氣） manner of carrying and conducting oneself; deportment ...
  • 率 : 率名詞（比值） rate; ratio; proportion
  • 貝葉 : （印度貝多羅 pattra 樹的葉子, 古代印度人用以寫佛經） pattra leaves
  • 概率 : [數學] probability; chance概率論 probability theory; theory of chances; 概率曲線 probability curv...
  1. The origin of the concept of obtaining posterior probabilities with limited information is attributable to thomas bayes.

    根據有限的信息得到的后定概率的概念最初是貝葉斯創造的。
  2. Compared with the regular rule - based expert system, the bayesian network based es can reason on the incomplete input information using the prior probability distribution ; the topological structure of the network being used to express the qualitative knowledge and the probability distributions of the nodes in the network being used to express the uncertainty of the knowledge, which made the knowledge representation more intuitively and more clearly ; applying the principle of the bayesian chaining rule, bidirectional inference which allow infer from the cause to the effect and from the effect to the cause can be achieved

    與一般基於規則的專家系統相比，貝葉斯網專家系統利用先驗概率分佈，可以使推理在輸入數據不完備的基礎上進行；以網路的拓撲結構表達定性知識，以網路節點的概率分佈表達知識的不確定性，從而使不確定性知識的表達直觀、明確；利用貝葉斯法則的基本原理，可以實現由因到果及由果到因的雙向推理。
  3. At last, this thesis figures out an event - based method of air threat assessment through the definitions of the events, the modeling accompanied with xml description of the model, the introduction of the functional architecture model of event correlation, the type of event correlation and the expressions of the theory of this technique, the event deleting and contracting on the data facet, the correlation between the events in causality by bayesian network and the probability reasoning, exemplifying and calculating of bayesian network employed in the construction of threat assessment model of air battle

    最後提出了一種基於事件的空戰威脅估計方法。對事件進行了定義、建模並用xml語言進行了數據描述;介紹了事件關聯功能結構模型;介紹了事件關聯類型及知識表達方式，從數據層進行了事件清理和壓縮，使用貝葉斯網路對因果事件進行關聯，建立了空戰威脅估計貝葉斯網模型、進行了貝葉斯概率推理及算例分析。
  4. Then, with the concept of accumulated failure probability, the proposed approach combines the least ? quares method with bayes " theorem, takes advantage of the parameter estimation for single weibull distribution to each derived subgroup data set, and estimates the parameters of each subpopulation. the estimates given by this paper also satisfy the maximum likelihood equation. the mean time to failure and the reliability estimation of the mixed population are given

    然後通過利用累積失效概率等概念，對每個導出的子組數據集聯合運用最小二乘法、貝葉斯定理和對單一威布爾分佈的參數估計法，從而得到每個子總體的滿足極大似然原理的參數估計，給出了該混合總體平均壽命和可靠度的估計。
  5. 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。
  6. Readers learn how to use the renowned bayesian theory of probability and other guideposts from outside the world of finance to adjust their strategies and react to new information

    讀者學習如何使用知名貝葉斯概率論和其他重要思想，從外部世界的財務調整自己的戰略和反應，以新的信息。
  7. An efficient implementation of this framework is presented, for segmenting two motions ( foreground and background ) using two frames. the expectation - maximization algorithm is used to determine the two motions and calculate the label probability for each edge. the best motion labeling for these regions is determined using simulated annealing

    針對前景和背景兩種運動分割的情況，本文給出了一種基於貝葉斯分割框架的有效實現，它使用最大期望（ em ）演算法來估算邊緣的標定概率，並通過模擬退火演算法來完成這些分割區域的最佳運動標定。
  8. The two - stage modeling method takes into account the characteristics of software project risk management and software metrics data, integrates qualitative knowledge and quantitative data. to study the software project iterative process risk ’ s bayesian network model, the definition of cyclic bayesian network is presented, probability convergence property of directed cycle in cyclic bayesian network is proved and probability inference method is put forward

    論文在軟體項目迭代過程風險的貝葉斯網路模型研究中，定義了有環貝葉斯網路，證明了有環貝葉斯網路中有向環的概率收斂性質，給出了有環貝葉斯網路的概率推理方法。
  9. Application of bayesian statistics inference techniques based on gis to the evaluation of habitat probabilities of bos gaurus readei

    的貝葉斯統計推理技術在印度野牛生境概率評價中的應用
  10. Comparing with non - bnyain methods, it ' s prominent featares lay in that it combines the prior and posterior information, which avoids the disadvantag of subjective bias caused by simply using the prior information only, of blind search caused by the incomplete sample information, of noise affection caused by simply using the sample information only if we choice a suitable priof, we can conduct the bayesian leaming effectively, so it fits the problems of data mining and machine leaming that possess charaters of probability and statistics, especially when the samples are rare

    與非貝葉揚方法相比，貝葉斯方法的特出特點是其學習機制可以綜合先驗信息和后驗信息，既可避免只使用先驗信息可能帶來的主觀偏見，和缺乏樣本信息時的大量盲目搜索與計算，也可避免只使用樣本信息帶來的噪音的影響只要合理地確定先驗，就可以進行有效的學習。因此，適用於具有概率統計特徵的數據採掘和機器學習（或發現）問題，尤其是樣本難得的問題
  11. Combined with the prior distribution of the model parameters and water quality observation data, joint posterior probability function which stands for the distribution characters was obtained by bayes ' theorem

    結合模型參數的先驗分佈和水質監測數據，通過貝葉斯定理計算獲得了表徵參數分佈規律的聯合后驗概率密度函數。
  12. Application of bayesian network and its probability reasoning to intelligent tutoring system

    貝葉斯網及其概率推理在智能教學中的應用
  13. While, study the scheduling bayesian network to model software project scheduling risk. the modeling method, related calculation and probability inference algorithm are presented

    在進度貝葉斯網路的研究中，給出了軟體項目進度風險的建模方法、模型中的相關計算以及概率推理演算法。
  14. In the paper, the models of uncertain reasoning are focused, such as the reasoning model of bayes probability, reliability theory, d - s evidence theory and neural network

    本文主要涉及的不確定推理模型包括主觀貝葉斯的概率推理模型，可信度理論推理模型，證據理論及其改進推理模型以及神經網路推理模型。
  15. 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。
  16. In the first chapter, the thesis illustrates the foundation and significance of this thesis and simply summarizes their researchful history and actualities of bn and cbr. in the second chapter, the thesis firstly explains the notion of bn, afterwards studies the application of bn in data - mining ( dm ) in detail and also studies the learning of the probability parameter and the structuring framwork of bn in the condition of the full data and the lacked data

    第一章，說明了本文的研究背景和意義並且簡單總結了貝葉斯網和範例推理的研究歷史和現狀。第二章，首先給出了貝葉斯網路的概念，然後詳細研究了貝葉斯網用於數據挖掘。分別對數據完整和不完整情況下，概率參數的學習和貝葉斯網結構的建立作了研究。
  17. Research on mail filter algorithm based on bayes probability model

    基於貝葉斯概率模型的郵件過濾演算法探討
  18. Later in this article, graham suggested building bayesian probability models of spam and non - spam words

    ）中， graham提議建立垃圾郵件和非垃圾郵件單詞的貝葉斯概率模型。
  19. In this model, the author puts forward the filter algorithm based on bayes distributing by researching the statistical distributing of the spam keys. at the same time, the rationality and the efficiency of the filter algorithm have been particularly analyzed in the model

    作者通過分析研究垃圾郵件關鍵詞的統計概率分佈，提出了基於貝葉斯概率模型的郵件過濾演算法，並對該演算法的合理性和復雜度進行了分析。
  20. The value of the statistical distributing of the spam keys can be also adjusted during the running of the system so that enhance the self - adaptation of the system. at last, the author tests the whole system and demonstrates this system is reasonable and correct by the testing data

    最後，作者對郵件防火墻系統進行了實驗測試，證明該系統方案設計是合理、可行的，基於貝葉斯概率統計分佈的郵件過濾演算法能有效提高垃圾郵件過濾的效率，具備一定的智能性和自適應性。
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