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In this work the mechanical properties of a highly alloyed cupronickel have been analyzed using a neural network technique within a Bayesian framework. In this way the mechanical properties can be represented as an empirical function of the compositional variables. This method has been used to analyze the relative contributions of the various elements to the mechanical properties. Whilst the method...
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