identification probability 中文意思是什麼

identification probability 解釋
命中概率
  • identification : n. 1. 認出，識別，鑒定，驗明（罪人正身等）。2. 【心理學】自居作用。3. 身分證。4. 【數學】黏合，同化。
  • probability : n 1 或有；或然性。2 【哲學】蓋然性〈在 certainly 和 doubt 或 posibility 之間〉。3 【數學】幾率，...
  1. After analyzing the character of risk, i introduce data mining method into risk management, to solve the contradiction between great capacity of data and lack of information, the methods include mathematics statistics and artificial neural network ( ann ). then, i study on the methods of risk management in risk identification, risk evaluation and risk disposal, what is advanced, fault tree analysis method based on fuzzy probability, stochastic simulation method and the topsis method based on interval number all consider the characteristic of risk. finally, i discussed the application of information system ( mis ) in project risk management, and developed a risk management information system

    論文在深入分析了風險特徵之後，將數據挖掘技術引入風險管理，用以解決海量數據與貧乏信息之間的矛盾，所採用的技術有數理統計和人工神經網路（ ann ）兩種方法；接著，論文對風險識別、風險評價、風險處理中的風險管理方法進行了研究，所提出的基於模糊概率的故障樹技術、隨機模擬技術和基於區間數的topsis方法都體現了風險管理的特點；最後，論文對信息系統（ mis ）在工程項目風險管理中的應用進行了探討，開發出一個風險管理信息系統。
  2. The probabilities of correct identification are combined across multiple peptide searches using a function that returns the maximum probability from consensus identifications, and penalizes non - consensual identifications

    肽段的正確或者錯誤鑒定都認為是肽段空間中的隨隨機事件，與一些參數相關，例如蛋白質長度，蛋白質的估計濃度，數據庫大小，數據集中鑒定的肽段數目。
  3. Again, a simple supported beam with stochastic mass density is used as an example. its statistics ( the mean value and the variance ) are calculated and compared with the theoretical values to verify the correctness of the used formulas. eventually this becomes the theoretical basis of the probability damage identification of the bridges

    3 .對于簡支梁橋，用該方法進行損傷識別，無論何種情況，識別結果都比較理想:對于有損傷單元，其單元損傷概率達到98 %以上;對于無損傷單元，其單元損傷概率一般都小於10 % ，可以認定，這些單元發生損傷的情況為小概率事件，即不發生損傷。
  4. The third part : according to the verified structural damage identification method and supposing the to - be identified parameters to be independent and have normal distribution, the scheme of identifying bridge structure damage is proposed by using the probability damage identification method. assume the zero - order, the first - order and the second - order perturbation statistics of the frequencies and the mode shapes of the bridge structures are known, and substitute them into the statistics property formulas of the frequencies and the mode shapes, as a result an objective function including the mean values and the variance of all the identified parameters is established. set

    對于連續梁橋，當損傷位置位於跨中附近時，大多數無損傷單元的損傷概率均在10 %左右，可作為小概率事件，不發生損傷，但與損傷單元相鄰的無損傷單元，其損傷概率達到20 %以上，很難被排除，只有對這些單元進行二次識別，才能得到比較可靠的計算結果;如果損傷位於支點附近時，則不會出現上述情況，對于無損傷單元，損傷概率都小於10 % ，不發生損傷，損傷識別結果
  5. From angle of prove, truth and exactness of scientific theory prove, identification to causality in fiction fact, and science own error probability and scientific probability direct against the issue of scientific precise, are analyzed

    從證明的角度，對鑒定實施中科學理論的真理性和正確性證明、擬制事實中的因果關系，並針對包括科學本身誤差幾率與科學的概率在內的科學確率問題作了分析。
  6. The system we developed is already practiced at blood transfusion in one medical center in southern taiwan, and we expect to leverage computerize procedures to help identification and authentication during the whole transfusion for ensuring transfusion safety, reducing the probability of medical errors, and providing high quality medical care

    本系統已實際運用於南部某醫學中心的?血作業，我們希望藉由電腦化作業?執?各項核對與辨?的工作，以確保輸血安全， ?低醫?疏失，提升醫?品質與病患安全。
  7. Based on the discussion the peculiarity of computer identification of tectonic soft coal seam, implemented the computer automatically identification of tectonic soft coal seam with well log of coal seam using the method of stratifying with slope - variance and probability statistics

    摘要在對構造軟煤分層計算機識別的特殊性進行探討的基礎上，應用斜率方差分層、概率統計計算的方法，實現了煤層段的測井曲我對構造軟煤分層的計算機「自動」識別。
  8. A probability updating methodand its applications in target identification

    一種概率更新方法及在目標識別中的應用
  9. The thesis, in the probability analysis and computation, considers the failure history of space frames and trusses, adopts the bound criterion and algorithms on the base of system ' s critical strength, and introduces the soft self - adaptation control bound into the identification of dominant failure modes ; at the same time, with the incremental load method and differential equalized recursive method, computes the limit - state function of failure mode and probability index precisely under no leaking the dominant failure modes

    文中在可靠性分析和計算部分，考慮空間剛桁架結構系統的失效演化歷程，採用基於系統臨界強度的約界準則和約界演算法，將柔性自適應控制邊界引入失效模式識別過程；同時，用荷載增量法和微分等價遞歸演算法相結合，確保在嚴格不遺漏主要失效模式的情況下，快速準確地求解失效模式的極限狀態方程和可靠度指標。
  10. The results show that bayes algorithm performs well in combining radar information for target identification because the need of prior probability is not too strict. but for bayes method, the robustness is not so well as that of d - s method

    結果表明， bayes方法對先驗信息的精確程度要求並不十分嚴格，能較好地解決雷達情報綜合問題，而d - s方法比bayes方法更具有穩健性，但是其收斂時間較長。
  11. The process of determining the qualitative and / or quantitative estimation, including attendant uncertainties, of the probability of occurrence and severity of known or potential adverse health effects in a given population based on hazard identification, hazard characterization and exposure assessment

    在危害的識別、危害的特徵描述和暴露評估的基礎上確定事件暴發的概率和嚴重性，或對健康產生潛在不良影響的定性和/定量評估的過程。
  12. The paper combines artificial neural network, fuzzy inference system, system identification, and does a thorough research on fuzzy - neural network. the research results are as follows : in this paper, we propose a new neuro - fuzzy systems with laplace ( probability density function ) membership function, and proved its universal approximation property by using weierstrass theorem. we get excellent modeling results for nonlinear systems by applying the new neuro - fuzzy model

    本文融合了人工神經網路、模糊推理系統、系統辨識等理論，並圍繞神經網路和模糊推理的結合體? ?模糊神經網路，展開了深入地研究，主要完成了如下研究工作：本文提出一種新型的帶laplace （概率密度函數）型隸屬函數的模糊神經網路模型，並應用微分中值定理和weierstrass定理證明它的通用逼近性。
  13. In the d - s evidence model, we provide two examples, the first case is client evaluation in the bank credit with d - s model, which can be compared with the model of probability. the second case is identification and classification in medical images, which use to explain the applied method

    證據理論推理模型給出了兩個應用實例，一是採用了證據推理模型的銀行信貸客戶評價案例與主觀貝葉斯方法進行比較，二是利用醫學圖像分類識別示例說明不確定推理的具體應用方法。
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