熵損失 的英文怎麼說
中文拼音 [shāngsǔnshī]
熵損失
英文
loss of entropy-
The admissibility theorem under symmetric entropy loss function
對稱熵損失函數下的一個可容許性定理的證明The class of distributions includes the weibull, burr - type x, pareto and beta distributions. a proper general prior density function is suggested, and predictive density functions are obtained in one - and two - sample cases when the history sample is a type ii double censored sample. illustrative examples are given
在type雙刪失數據場合下，討論了雙參數burr - type分佈參數的貝葉斯估計，在所取的損失函數分別為平方損失， linex損失，熵損失函數下得到了參數的貝葉斯估計，並且給出一種近似演算法。In order to accurately calculate the available energy dissipation resulted from the steam flowing through a restrictive device, a new view point for measuring energy in steam piping network system has been put forward, i. e. a model for computing the available energy dissipation has been obtained through entropy equation in occurrence process of the resistance, which is deduced from steam condition equation of iapws - if97
為了準確計算蒸汽流經阻力件產生的可用能損耗，提出了蒸汽管網系統能量計量的新觀點，即通過iapws - if97的蒸汽狀態方程，推導出阻力發生過程的熵方程，得到可用能損失計算模型。The mixing degree model was established to study the mixing progress of primary and secondary flow. the loss elements of all zones were deeply analyzed and thus the quantitative loss models based on total pressure loss and entropy increase respectively were constructed. the results show that the performance loss magnitude and distribution in ejecting mode of rbcc can be better described by the quantitative loss model expressed by entropy increase
提出用摻混度模型來研究一次流與二次流的摻混程度，並深入分析了各流動區域的損失因素，建立了以總壓損失和熵增分析為基礎的損失量化分析模型，計算的結果表明，採用熵增模型描述的損失因子能量化反應引射摻混損失的分佈和大小。Parameter estimation of exponential distribution under q - symmetric entropy loss function
對稱熵損失函數下指數分佈的參數估計Estimation of scale parameter of normal distribution under q - symmetric entropy loss function
對稱熵損失函數下正態總體刻度參數的估計Estimation of order means of two sample distribution exponential under symmetric entropy loss
對稱熵損失下兩個指數總體均值的序約束估計To the problem that finding rules in enormous data is very time - consumable and the expansibility of existed algorithms is not very good, the thesis proposes a new method to discompose large data table based on the concepts of positive region and the importance of attribute in rough set theory. existed algorithms of rule deduction can be applied directly on the tree structure obtained by partition and the times for computation will be reduced observably. validation of information entropy on the partition structure shows that the partition of data table will not lead to the loss of information, while the computing speed increases at the same time, which reflects the practicability and rationality about the partition of large data table
針對海量數據處理起來極為耗時，現有演算法拓展性較差的問題，基於rough集理論中的集合正域概念以及由此定義的屬性重要性概念，提出一種大型數據表分解演算法，現有的規則歸納演算法可直接在分解得到的樹型結構上應用，將大大降低知識發現的時間，並從信息理論的角度利用信息熵概念對該分解結構進行了驗證，分析了這種分解的實用性及合理性，揭示了這種分解結構在提高計算速度的同時不會損失信息量。2 ) by analyzing the information and conditional information description mechanism of system states, the problem of stochastic model reduction is investigated based on state aggregation. the information loss and conditional information loss between the full - and reduced - order models are measured by entropy, while the independence and conditional independence within me components of aggregated state are measured by kullback - leibler information distance. several model reduction methods for stable and unstable linear systems are derived by employing two criteria to get aggregation matrices : the minimal information loss and the maximal independence
2 ）分析了隨機系統狀態空間模型中的信息和條件信息描述機制，以shannon熵為手段描述線性系統模型降階過程中的信息和條件信息損失，以kullback - leibler信息作為衡量降階模型狀態向量各分量之間統計獨立性的測度，針對穩定和不穩定系統研究基於狀態集聚的模型降階問題：分別運用最小信息損失準則和最大獨立性原則，得出幾種狀態集聚的信息論方法，並討論降階模型的性質、階次的確定、系統噪聲分佈特性等問題。分享友人