Research on interactive color design method of cultural creative product driven by group consensus

Aiming at assisting the color design of cultural creative product and outputting color schemes that correspond to multi-user image preference effectively, an interactive color design method driven by group consensus was proposed in this paper. Firstly, the triangular fuzzy number was used to quantitatively descript users' image preference and a consensus degree model of group users' image preference was constructed. By studying the process and basic principles of interactive genetic algorithms, the interactive evolution operation for cultural creative product color design was then implemented based on the group consistency of decision-making combined with the triangular fuzzy number, which can help generate cultural creative product color schemes that satisfy group consensus and satisfaction. Next, the color aesthetic measure model was used to rank and select the final product color design schemes. Finally, taking the color design of terracotta warriors' statue as an example, it is verified that the proposed method can effectively integrate the image preference of group users, and assist designers to better conduct cultural creative product color design with the consistent results of multi-user decisions.

Combining Users’ Cognition Noise with Interactive Genetic Algorithms and Trapezoidal Fuzzy Numbers for Product Color Design

Product color plays a vital role in shaping brand style and affecting users’ purchase decision. However, users’ preferences about product color design schemes may vary due to their cognition differences. Although considering users’ perception of product color has been widely performed by industrial designers, it is not effective to support this activity. In order to provide users with plentiful product color solutions as well as embody users’ preference into product design process, involving users in interactive genetic algorithms (IGAs) is an effectual way to find optimum solutions. Nevertheless, cognition difference and uncertainty among users may lead to various understanding in line with IGA progressing. To address this issue, this study presents an advanced IGA by combining users’ cognition noise which includes cognition phase, intermediate phase, and fatigue phase. Trapezoidal fuzzy numbers are employed to represent uncertainty of users’ evaluations. An algorithm is designed to find key parameters through similarity calculation between RGB value and their area proportion of two individuals and users’ judgment. The interactive product color design process is put forward with an instance by comparing with an ordinary IGA. Results show that (1) knowledge background will significantly affect users’ cognition about product colors and (2) the proposed method is helpful to improve convergence speed and evolution efficiency with convergence increasing from 67.5% to 82.5% and overall average evolutionary generations decreasing from 18.15 to 15.825. It is promising that the proposed method can help reduce users’ cognition noise, promote convergence, and improve evolution efficiency of interactive product color design.

Optimization of the Sound of Electric Vehicles According to Unpleasantness and Detectability

Electric Vehicles (EVs) are very quite at low speed, which can be hazardous for pedestrians. It is necessary to add warning sounds but this can represent an annoyance if they are poorly designed. On the other hand, they can be not enough detectable because of the masking effect due to the background noise. In this paper, we propose a method for the design of EV sounds that takes into account in the same time detectability and unpleasantness. It is based on user tests and implements Interactive Genetic Algorithms (IGA) for the optimization of the sounds. Synthesized EV sounds, based on additive synthesis and filtering, are proposed to a set of participants during a hearing test. An experimental protocol is proposed for the assessment of the detectability and the unpleasantness of the EV sounds. After the convergence of the method, sounds obtained with the IGA are compared to different sound design proposals. Results show that the quality of the sounds designed by the IGA method is significantly higher than the design proposals, validating the relevance of the approach.