基于信息熵和最小偏差的产品意象评价方法

Product image evaluation method based on information entropy and minimum deviation

为减少认知不确定性对感性意象评价结果的影响,提出一种基于信息熵和最小偏差的产品意象评价方法。根据设计任务确定目标意象,进行方案设计,经感性意象调查获取初始评价矩阵。以最小偏差计算设计方案综合评价偏离度,使其同时满足个体缺失最少和群体综合效益最大。使用信息熵对认知不确定性进行表达,依据最大信息熵原理,构建产品意象评价约束条件,保证评价权重信息的完整性。建立产品意象评价模型,对设计方案进行意象综合评价计算,优选合适的方案。以数控机床意象造型设计方案评价为例,验证了该方法的合理性和可行性。

In order to reduce the influence of cognitive uncertainty on kansei image evaluation results, a product image evaluation method was proposed based on information entropy and minimum deviation. The target image was determined according to the design task. The scheme design was carried out, and the initial evaluation matrix was obtained through the kansei image survey. The comprehensive evaluation deviation degree of the design scheme was calculated with the minimum deviation, so as to satisfy the maximum comprehensive benefit of the group and the minimum individual defects. The information entropy was used to express the cognitive uncertainty. The product image evaluation constraints were constructed according to the principle of maximizing information entropy to ensure the integrity of the evaluation weight information. A product image evaluation model was established to calculate a comprehensive image evaluation of the design scheme for selecting a suitable scheme. The image modeling design scheme evaluation of CNC machine tools was taken as an example to verify the rationality and feasibility of the method.