The process of motorcycle seat styling is a grey system with partially known and partially unknown information and is influenced by various factors. In this study, Grey Modelling (GM)(1,1) is used to predict the style of a motorcycle seat, and the shape features of the seat are extracted via morphological analysis and are parameterized. The process of shape evolution is established, and the modelling characteristics are predicted by GM(1,1). The kansei study is performed using five adjectives describing the seat styles to establish the equation of kansei regression analysis. The regression analysis is employed to modify predictive modelling. A certain brand of motorcycle seats is modelled to analyse and verify the feasibility and scientific applicability of adopting GM(1,1) in predicting motorcycle seat styling, which provided a feasible and effective reference for the motorcycle seat design.

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ABSTRACT3D modeling for Archaeology requires to easily model scenes by letting users evaluate a parametric specification of archaeology-oriented gestures, then modify and reevaluate the specification to produce various restitution hypotheses. But the current modeling tools that support reevaluation mechanisms are not dedicated to Archaeology. The Jerboa library, based on graph transformations rules, is well suited for creating operations fitting the needs of archaeologists. But it does not any support reevaluation mechanism and especially the persistent naming system, that is used to identify the entities of the initial model and match them with entities of the reevaluated model. In this paper, we extend Jerboa with a new application-independent persistent naming model, which is more general and homogeneous than other solutions found in the literature and is the first one to handle parametric specification edition.