{"id":37531,"date":"2021-05-09T09:58:09","date_gmt":"2021-05-09T06:58:09","guid":{"rendered":"https:\/\/ihcoedu.uobaghdad.edu.iq\/?p=37531"},"modified":"2021-05-26T13:57:51","modified_gmt":"2021-05-26T10:57:51","slug":"%d9%82%d8%b3%d9%85-%d8%a7%d9%84%d8%b1%d9%8a%d8%a7%d8%b6%d9%8a%d8%a7%d8%aa-%d9%8a%d9%86%d8%a7%d9%82%d8%b4-%d8%b1%d8%b3%d8%a7%d9%84%d8%a9-%d9%85%d8%a7%d8%ac%d8%b3%d8%aa%d9%8a%d8%b1-%d8%aa%d8%a8%d8%ad-13","status":"publish","type":"post","link":"https:\/\/ihcoedu.uobaghdad.edu.iq\/?p=37531","title":{"rendered":"\u0642\u0633\u0645 \u0627\u0644\u0631\u064a\u0627\u0636\u064a\u0627\u062a \u064a\u0646\u0627\u0642\u0634 \u0631\u0633\u0627\u0644\u0629 \u0645\u0627\u062c\u0633\u062a\u064a\u0631 \u062a\u0628\u062d\u062b \u0641\u064a \u0627\u0644\u062a\u0642\u062f\u064a\u0631 \u0627\u0644\u0645\u062a\u0642\u0644\u0635 \u0644\u0645\u0639\u0648\u0644\u064a\u0629 \u0646\u0638\u0627\u0645 \u0646\u0645\u0627\u0630\u062c \u0627\u0644\u0627\u062c\u0647\u0627\u062f \u0627\u0644\u0645\u062a\u0627\u0646\u0629"},"content":{"rendered":"

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    \n

    On Shrinkage Estimation of System Reliability in Stress Strength Models<\/span><\/h3>\n

    By Iman Ghaji Jebur<\/span><\/h3>\n

    Supervised by Lec.Dr. Bayda Atiya Kalaf<\/span><\/h3>\n

    Abstract<\/span><\/h3>\n

    The stress-strength model is one that is used to compute reliability. It is found to be useful in situations whenever the reliability of a system or component is defined by the probability that a random variable of strength is greater than the random variable of stress, while it makes intuitive sense that a component is deemed to have failed when its strength is lower than the applied stress<\/span><\/h3>\n

    Therefore, the purpose of this thesis was included in three pivots. The first one is to derive the system reliability formula in the stress resistance (S-S) model when strength X and stress Y are independent random variables and it follows the General Inverse Rayleigh Distribution with shape parameters for five types of models<\/span><\/h3>\n

    The first modelincludes a system containing one component that has a strength X subject to stress Y, the second model ), includes a system that contains one component with a strength of X that is subject to minimum and maximum stress, respectively, the third model \u00a0contains three consecutive components that have strengths of X and are subject to the stress of Y, the fourth model contains three parallel components that have strengths of X and are subject to stress Y, and the last form for the multicomponent system (S-out of-K) the strength X works when at least S of K are working; (1\u2264 S\u2264 K) subject to a common stress Y ((\u00a0 exceed\u00a0 Y), when X and Y follow GIRD<\/span><\/h3>\n

    The second pivot concern with an estimate of the system reliability of the five proposal types stress-strength models via different estimation methods under the name: Bayesian estimation and use three types of shrinkage methods. Since, recently with advances in computation and methodology, researchers are using Bayesian methods to solve an increasing variety of complex problems. In many applications, Bayesian methods provide important computational and methodological advantages over classical techniques\u00a0<\/span><\/h3>\n

    Finally, the third axis consists of the comparisons of the proposed estimation methods using the Mote Carlo simulation based on the criteria of mean squared error.The result analyses of the shrinkage estimation methods showed that the shrinkage functions estimator was the best at most since has the least mean squared error than the other methods and followed by the other shrinkage estimator<\/span><\/h3>\n

    <\/h3>\n

    <\/h3>\n

    <\/h3>\n

    <\/h3>\n

    <\/h3>\n

    <\/h3>\n

    <\/h3>\n

    <\/h3>\n

     <\/p>\n

     <\/p>\n","protected":false},"excerpt":{"rendered":"

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