基于用户意象偏好的轮毂款型推荐方法研究

发布时间：2018-04-11 11:15

本文选题：轮毂造型 + 意象偏好　；参考：《燕山大学》2016年硕士论文

【摘要】：目前,传统的轮毂造型设计开发方法凸显出一种弊端,造型方案的最终确定基本凭借设计师和决策者的直觉判断,这就导致了设计的轮毂产品不能很好的迎合市场中广大用户的审美需求和意象偏好。为了使轮毂造型能够更好的满足用户的个性化需求,需要一种能够将用户意象偏好引入到轮毂造型设计过程中的设计方法,通过运用这种方法达到破译用户的感觉编码,并将其转化为轮毂造型设计变量的目的。本文提出了如何将用户的意象需求引入轮毂造型设计,并将其转化为造型形态,使最终设计出的轮毂符合用户意象需求的问题。以用户意象偏好的轮毂款型推荐方法作为研究目标,结合感性工学、计算机辅助等技术,将用户对轮毂的意象偏好或感觉准确地转变成轮毂的设计变量要素,进而能够更加有效的对用户的意象偏好与轮毂造型设计变量之间的映射关系进行探索和研究,以这种映射关系为依据,最终设计出的轮毂造型就更能符合用户的意象偏好。本文采用感性工学、统计学、机器学习等领域的相关知识构建了一个行之有效的推荐系统,来最大化的满足用户的意象需求。首先,对轮毂的关键造型特征以设计变量的形式表现。其次,以感性工学(Kansei Engineering)理论作为基础,利用调查问卷的数据建立轮毂的评价量表。再次,利用支持向量机(Support Vector Machine)方法构建用户意象语汇与偏好之间关系模型和轮毂设计变量与偏好之间的关系模型。最后,通过遗传算法(Genetic Algorithm)求出满足用户意象需求的最优的轮毂造型。本研究结果对轮毂设计过程中有效把握用户意象偏好,设计符合用户意象需求的轮毂造型具有一定的参考价值及借鉴意义。
[Abstract]:At present, the traditional wheel hub modeling design development method highlights a kind of drawback. The final determination of the modeling scheme basically depends on the intuitive judgment of the designer and the decision maker.This leads to the design of hub products can not meet the needs of the majority of users in the market aesthetic needs and image preferences.In order to make hub modeling better meet the individual needs of users, it is necessary to introduce user image preference into the design process of hub modeling, which can be used to decode the user's sensory coding.And the purpose of transforming it into wheel hub modeling design variable.In this paper, the problem of how to introduce the user's image requirement into the hub modeling design and transform it into the shape form is put forward, so that the final design hub meets the user's image requirement.In this paper, the user's image preference of hub model recommendation method is taken as the research goal, and combining with perceptual engineering and computer aided technology, the user's image preference or feeling towards the hub is accurately transformed into the design variable element of the hub.Furthermore, the mapping relationship between user's image preference and hub design variables can be explored and studied more effectively. Based on this mapping relationship, the final design of hub modeling can be more in line with the user's image preference.In this paper, an effective recommendation system is constructed with the knowledge of perceptual engineering, statistics, machine learning and so on, to maximize the image needs of users.First, the key modeling features of the hub are expressed in the form of design variables.Secondly, based on Kansei engineering theory, the evaluation scale of hub is established by using the data of questionnaire.Thirdly, the relationship model between user image vocabulary and preference and the relationship model between hub design variables and preferences are constructed by using support vector machine support Vector machine method.Finally, genetic algorithm is used to obtain the optimal hub modeling to meet the needs of user image.The results of this study have a certain reference value and reference significance for the wheel hub design process to effectively grasp the user image preference and design the hub modeling which meets the needs of the user image.
【学位授予单位】：燕山大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.3

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