Key Laboratory of Oil and Gas Equipment, Ministry of Education, Southwest Petroleum University, Chengdu 610500, China.
School of Mechatronic Engineering, Southwest Petroleum University, Chengdu 610500, China.
Comput Intell Neurosci. 2019 Jan 13;2019:1860921. doi: 10.1155/2019/1860921. eCollection 2019.
In order to design a cultural and creative product that matched the target image, this paper proposed to use EEG, interactive genetic algorithm (IGA), and back propagation neural network (BPNN) to analyze the users' image preferences. Firstly, the pictures of cultural elements were grouped according to the pleasantness value and emotional state by PAD emotion scale, and the brain waves induced by the pictures of cultural elements with different pleasure degree were recorded by electroencephalograph. Then, the preference of cultural elements was obtained according to the theory of frontal alpha asymmetry. Secondly, the semantic difference method was used to carry out questionnaire survey to users, and the factor analysis method was used to statistically analyze the survey results to extract the perceptual image semantics of users for cultural and creative products. Thirdly, an interactive evolutionary design system based on IGA and BPNN was constructed. According to the cultural elements preferred by users, the designer designed the initial set of morphological characteristics, and the fitness value was determined according to the degree of user preference for the image semantics. Meanwhile, in order to reduce the fatigue caused by users' interaction evaluation, BPNN was introduced to simulate artificial evaluation. Finally, the proposed method was verified by the practice of flavoring bottle design. User preference requirement could be used as feedback information to help designers understand users' design emotional need and generate design schemes that satisfied the users' perceptual image.
为了设计符合目标形象的文化创意产品，本文提出采用脑电图（EEG）、交互式遗传算法（IGA）和反向传播神经网络（BPNN）分析用户的形象偏好。首先，通过 PAD 情绪量表将文化元素的图片按愉悦值和情绪状态进行分组，并用电极记录不同愉悦度的文化元素图片所引起的脑电波。然后，根据额α不对称理论得出文化元素的偏好。其次，采用语义差异法对用户进行问卷调查，并采用因子分析法对调查结果进行统计分析，提取用户对文化创意产品的感性形象语义。第三，构建基于 IGA 和 BPNN 的交互式进化设计系统。根据用户偏爱的文化元素，设计师设计初始形态特征集，并根据用户对形象语义的偏好程度确定适应度值。同时，为了减少用户交互评价带来的疲劳，引入 BPNN 模拟人工评价。最后，通过调味瓶设计实践验证了该方法。用户的偏好需求可以作为反馈信息，帮助设计师了解用户的设计情感需求，并生成满足用户感性形象的设计方案。
