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This paper reports a series of investigations into the robustness of designs that underlie selected service discovery systems.
The procedure is applied to the design of composite yacht hulls comparing the robustness of designs aimed at satisfying a range of performance and cost requirements.
In this study, a new criterion, called minimum breakdown criterion, is proposed to quantify the robustness of designs in blocks of size two.
Further, we investigate the robustness of designs with respect to initial parameter estimates and Copula function, and also show the performance of compound criteria within this bivariate binary setting.
The characterization of robustness of designs are given under the different possible true models within the class of models considered under the proposed J and I optimality criterion functions.
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The hazard rating of a material determines the robustness of design verifications.
Moreover, effects of uncertainties are also investigated under several cases, indicating good robustness of designed suspension systems.
The proposed approach was implemented on automobile parts to determine the effectiveness and robustness of designed algorithm.
Based on an order relation of interval number, the uncertain objective function is transformed into two deterministic objective functions, in which the robustness of design is considered.
Both the stability and the robustness of designed models are evaluated by using a variant of Monte-Carlo cross-validation (MCCV) with 1000 randomly chosen validation sets.
In this paper, we propose a new resistance factor calibration approach to address this dilemma by considering "feasibility robustness" of design in the calibration process.
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