This paper puts forward a designing method of Dependable Network System Security Risk Diagnosis (DSSRD). It gets reduced information table, which implies that the number of evaluation criteria is reduced with no information loss, and then, this table is used to develop classification rules and infer appropriate parameters. It’s capable of overcoming several shortcomings in existing diagnosis methods, such as a dilemma between stability and redundancy. The average speed of training in DSSRD is almost twice fast as that in SMO. The experiment implemented by this method shows a good diagnostic ability.
In order to be considered in the calculation of punching force of cold die random distribution of material properties, meanwhile including success and failure punching during the gradual change process in the calculation. Based on probabilistic fuzzy reliability point of view, the success or failure determination will be extended to fuzzy events. Based on fuzzy reliability, the punching force of cold die calculation method will be also given when taking the impact of random distribution of material properties into account. Related analysis formulae and the fuzzy criterion of success or failure of punching are established and derived. Through which, design and engineering process are integrated, the designer will be more reliably to predict the success or failure of the punching during the design stage. The processing error of lack of statistical data and the objectivity of the success or failure determination criterion will be easily solved. Economy cost and reliability design of geometrical curve design will be also considered.
In order to foresee the influence of random processing errors on geometric curve in design stage, meanwhile including success and failure process during the gradual change process in the forecast. Based on probabilistic fuzzy reliability point of view, the success or failure determination will be extended to fuzzy events. The geometric curve deign method will be also given when taking the impact of random engineering error into account. Related analysis formulae and the fuzzy criterion of success or failure of designing the curve process are established and derived. Through which, design and engineering process are integrated, the designer will be more reliably to predict the success or failure of the geometric curve design during the design stage. The processing error of lack of statistical data and the objectivity of the success or failure determination criterion will be easily solved. Economy cost and reliability design of geometrical curve design will be also considered.
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