A systematic method for color planning in product design

A quantitative approach for color planning in product design is addressed in this article. the color image that a product has is quantified by using the membership function of a fuzzy set. the color plan for designing an ice shaver is used as an example to show the procedure. the Hue and Tone System and the Color Image Scale are used to transform colors into images or images into colors. the composite operation for fuzzy sets is used to simulate a color projection technique to get the semantic equivalence of words and colors. A computer program is built to get the membership functions between the colors and image words. the membership functions are arranged by size and suggested to the designer to help make a decision on what color should be used. In this manner, the psychology of customers can easily be captured by the designer, consequently increasing the efficiency of the decision process. Though a simple product is taken as an example here, this systematic method can be used to design other more complicated products. In addition, the results can be used to investigate the color psychology.     

Pattern retrieval of yarn-dyed plaid fabric based on modified interactive genetic algorithm

With the development of perceptual consumption, consumers sometimes cannot explicitly describe the purchase demands or only based on impression, like the color perception and aesthetic experience. Based on the consumer's expression, it is difficult to design a new fabric by repeated proofing to meet the consumer's demands. To retrieve the existing patterns incorporating human intuition and emotion, this study proposed a novel pattern retrieval method of yarn-dyed plaid fabric using modified interactive genetic algorithm. Each pattern was encoded based on the design elements and visual features were extracted to bridge the semantic gap between the designer and the consumer. Survival of the fittest and two special mutation operators, addition and deletion, were designed to increase the diversity of the generations. During the evolution, the generated patterns were replaced by the most similar patterns in the database based on visual features. Experimental results showed that the proposed scheme is feasible and effective to extract the consumer's preferences and retrieve satisfactory patterns, helping the factory obtain the process sheet to guide production and save labor and material resources.     

Multiemotional product color design using gray theory and nondominated sorting genetic algorithm-III

When users select products, they consider the emotional experience resulting from the color of the product. However, the emotional demands of users for product color are multidimensional and diverse. It is very important yet difficult to accurately grasp multiemotional image requirements and effectively convert them into design elements. Therefore, multiemotional product color design (MEPCD) has become a very important and challenging research topic. In this article, a novel MEPCD system using gray theory (GT) and nondominated sorting genetic algorithm-III (NSGA-III) is proposed to effectively solve the MEPCD problem. First, the image perception spaces of users, which exist in different emotional dimensions, were collected using factor analysis and the semantic differential technique. Then, GT was used to establish a multidimensional emotional product color image evaluation model. Finally, NSGA-III was used to optimize and design a multiemotional color scheme for a product. Furthermore, according to actual conditions, an MEPCD system was established based on the proposed method. The design case study shows that the method and design system proposed in this article have a certain range of applicability and can effectively improve the practicality of MEPCD.     

Research on color optimization of tricolor product considering color harmony and users' emotion

There are few studies on the tricolor design optimization, and the influence of color-area ratio on users' emotion has been ignored. This article aims to achieve multiobjective optimization of tricolor product color design. Two modes of color-area ratio are put forward. Using the proposed method of generating tricolor schemes, 368 tricolor schemes of the representative baby carriage are designed. Through questionnaire survey, color images are screened, and combined with correlation analysis and factor analysis, five perceptual features of color design are determined as “Order,” “Excitement,” “Temperature,” “Color harmony,” and “Users' emotional preference.” From two perspectives of color information processing, radial basis function neural networks are used to construct two emotional evaluation models. By integrating the radial basis function neural networks and a genetic algorithm, this study achieves multiobjective optimization of tricolor product color design for two optimization objectives of color harmony and users' emotional preference. Verification results show that the optimization schemes are significantly better than other schemes. Due to similar product characteristics, children's electric car is utilized to verify the generalization capability of the optimization method proposed in this article. It has been demonstrated that the optimization schemes achieve higher scores than randomly selected color schemes and the actual subjective scores match with the predicted scores computed by the color optimization method.     

Application of genetic algorithm to color recipe formulation using reactive and direct dyestuffs mixtures

Color reproduction is a science in constant development. In this article, a new model to solve the color recipe prediction problem using a genetic algorithm is proposed. The objective is to optimize the color recipe prediction stage by determining the dyes to use in a mixture and their respective proportions to reproduce the target color. Two ranges of dyes were used for dyeing 100% cotton woven fabrics: three reactive dyes (CI Reactive Red 238, CI Reactive Yellow 145, and CI Reactive Blue 235) and four direct dyes (CI Direct Orange 34, CI Direct Red 227, CI Direct Blue 85, and CI Direct Black 22). The criterion of optimization, in reproducing the desired shades, is to minimize the CMC color difference between the desired reference color and the color resulting of the predicted recipe. The proposed algorithm revealed good results with small CMC color differences between target and reproduced colors. The effectiveness of the algorithm was also evaluated and proven by calculating errors between the predicted concentrations in the proposed recipes and the actual concentrations.     

基于改进的遗传算法设计萃取精馏萃取剂

将Mod.UNIFAC基团贡献法与改进的遗传算法相结合,进行萃取精馏萃取剂的分子设计。采用了一种简单易行的新编码方案,使合成的分子形式简单,便于链接数据库计算各种性质。提出了跨代精英选择策略,错位交叉算子,滞后变异算子,使设计出的分子结构稳定且形式多样,有效地避免了遗传算法不易得到全局最优解和容易提前收敛的问题。给出了分子设计的主要流程和方法,并编制了相应的计算机程序,将其应用于丙酮-甲醇体系,得到了水和乙二醇等萃取剂。结果表明,文中提出的方法对相对挥发度的预测精度高于文献值,同时检验了该方法的可靠性。     

Visual customization: Diversity in color preferences in the automotive interior and implications for interior design

Evolving multimodal mobility needs influences established human–product relationships and requires a deeper insight into color preferences for car interiors. Hence, a study was conducted in which 204 members of a web contest created 1,265 designs. After a peer‐evaluation process, 53 most‐appreciated and 34 least‐preferred interior color compositions were identified and compared to identify patterns in color choices. Besides, visual lightweight design by layering of large interior components such as the seat, a modest use of color and patterns accompanied by repetition and the framing of the entire interior to create a feeling of spaciousness were found. Additionally, differences in the type of color between most and least favored color designs were found. Brown and beige occur more frequently among the top‐ than the worst‐rated designs. Larger surfaces are favored in lighter hues and smaller components in darker hues.     

Bayesian analysis of color preferences: An application for product and product line design

When choosing which colors to offer in their product lines, firms often rely upon consumer preference models that do not account for the heterogeneity of their target market and do not consider the trade‐offs consumers are willing to make for different color options. For this research we used visual conjoint analysis to assess preference for backpack color and then modeled respondent utilities with a Bayesian hierarchal multinomial logit model. This provided counter intuitive results in which product line color options are not additive but each color changes depending on the number of options the firm is willing to offer and that colors which seem to dominate secondary preferences within a target market may not be the best colors to choose for product line expansion. © 2015 Wiley Periodicals, Inc. Col Res Appl, 41, 445–456, 2016     

Preference for accent and background colors in interior architecture in terms of similarity/contrast of natural color system attributes

Color combination criteria are said to entail an affective response in interior design. We investigated the color combination criteria that orient the preference of current observers, after Le Corbusier's 1931 Salubra keyboards. We explored the similarity/contrast in Natural Color System (NCS) hue, blackness, and chromaticness in 312 combinations with four colors, two backgrounds and two accent colors, coming from 43 individual colors, on the walls of a simulated interior of a bedroom from the Swiss Pavilion (Le Corbusier, 1930-1931). Participants were 644 students of architecture and interior design in Western Europe and Near East, who evaluated with a Likert scale their preference for virtual images via an online survey. Results indicate that the most preferred color combinations are those with hues closer in the color wheel, being the similarity between hues in the backgrounds more important than in the accent colors, and with NCS B30G to G as the most preferred hues. Observers preferred color compositions with blackness under 10% and similar blackness between the two background colors, together with a certain blackness contrast between these background colors and the two color accents. Similarly, observers liked color compositions with low chromaticness and low chromaticness difference among the four colors of the composition.     

汽-液-固流动沸腾系统混沌时间序列的遗传算法全局建模

与系统的平均特性建模研究相比,系统的时间序列建模工作更富挑战性,也更具有意义.最近的研究表明,汽-液-固三相流动沸腾系统的动力学行为具有混沌特征,因此,本文从非线性视角出发,开展系统物理量的时间序列建模研究.根据实验测得的反映系统非线性演化信息的汽-液-固三相流动沸腾系统的壁温时间序列数据,采用遗传算法全局建模方法,建立了描述该系统非线性动力学行为的时间序列迭代形式的数学模型,并将模型计算结果与实验数据进行了比较.结果表明,采用遗传算法全局建模方法所建立的模型,能够较好地描述汽-液-固三相流动沸腾系统的非线性动力学行为,模型计算值与实验数据吻合良好.     

基于改进遗传算法的PEMFC电堆温度模型建模

针对质子交换膜燃料电池（PEMFC）系统过于复杂、难以建模,而已建立的数学模型由于电堆使用的材料、结构不同,模型参数相差甚远,无法统一给出一个具有代表性的高精度的PEMFC电堆模型,难以满足PEMFC控制系统设计和应用的要求.本文从实际应用角度出发,利用传热学、流体动力学知识建立了一个千瓦级的PEMFC电堆温度模型.由于模型中一些关键参数无法由实验精确测出,但它们对模型精度的影响极大,所以需要找出一个能够高精度辨识模型参数的方法来解决这个问题.文章中提出的改进遗传算法具有良好的全局和局部的搜索、优化能力,能够高精度地辨识这些参数.仿真和实验结果验证了模型的实用性和可靠性.     

基于遗传算法的低噪声轮胎花纹节距排列的优化方法

介绍了遗传算法在轮胎花纹节距排列低噪优化设计中应用的方法与步骤。将节距作为基因进行编码,随机生成一个初始群体,然后进行选择,交叉,变异和再生等遗传操作,用适应度函数考核染色体个体的适应度,直至遗传操作收敛到最优解。用遗传算法进行了低噪优化实例分析。结果表明,该算法具有良好的收敛性和降噪优化效果,为轮胎花纹其它设计参数的低噪优化提供了一个先进、实用和科学的研究思路。     

基于遗传算法和粒子群优化算法的电力系统无功优化

从数学的角度分析,电力系统无功优化是一个多变量、多约束、非连续性的混合非线性规划问题,因此,优化过程十分复杂.以减少有功网损为目标函数建立电力系统无功优化计算的数学模型,基于遗传算法和粒子群优化算法,提出一种新颖的混合策略来求解无功优化问题.IEEE 6和IEEE 14节点系统的仿真计算结果表明:与单一的遗传算法或粒子群优化算法相比,该混合策略在优化效果方面具有明显的优势.     

基于全局优化改进混沌粒子群遗传算法的物料平衡数据校正

结合遗传算法（GA）和粒子群算法（PSO）的优点以及混沌运动的特性,提出了加入混沌扰动的混沌粒子群遗传算法（DCPSO-GA）,并使用5个高维非线性测试函数考察全局优化混合算法的性能。DCPSO-GA解决了在寻优搜索时出现的停滞现象,扩大了全局优化的搜索空间,丰富了粒子的多样性,且不需要函数梯度信息。测试结果证明,针对本文的5个测试函数DCPSO-GA能找到全局最优解,其收敛速度很快,大大减少了计算量。而且,经过与其他相关算法比较可知,当总的目标函数调用次数较接近或更少时,改进算法不论在计算精度还是收敛速度上,均有很大的提高。并将DCPSO-GA算法应用到重油裂解参数估计和预测中,测试结果证明,其提高了参数估计和预测的准确性,降低了误差,能有效找到全局最优解,收敛速度快,大大减少计算量。     

基于流程模拟的常减压装置过程操作与生产计划集成优化

传统的炼油企业生产计划优化与过程操作优化往往是分离的, 从而造成生产计划优化系统制定出的生产方案可能在实际的生产装置操作上无法实现的情况。为了确保石化企业生产计划制定的方案可行的同时实现过程装置操作优化, 基于流程模拟软件建立了常减压蒸馏装置生产计划与过程操作的集成优化策略, 并提出了该优化策略的有效寻优方法。该方法通过流程模拟软件验证生产计划的可达性, 不断修正生产计划关键变量的优化区间, 在求得生产计划最优解的同时确定装置的工艺操作条件。以某炼油厂常减压蒸馏装置炼油为例验证提出的集成优化方法, 案例证明该集成策略不仅确保生产计划在实际生产的可操作性, 还得到了生产计划与过程装置操作的同步优化。     

基于神经网络-遗传算法优化生物柴油制备工艺

根据生物柴油制备的实验数据,用人工神经网络(ANN)的反向传播(BP)算法建立了生物柴油转化率神经网络预测模型,提出了适宜的人工神经网络拓扑结构,讨论了BP算法中学习速率、动量系数及过拟合现象对网络的影响。实验数据检验表明,ANN方法能准确地关联生物柴油制备工艺条件与转化率的关系,转化率预测平均相对误差为1.917%,复相关系数R为0.9996;该神经网络预测模型用遗传算法优化,得到了最佳生物柴油制备条件。     

基于遗传算法的干气密封双向槽统一模型与参数优化

通过提出表征能力更强的新型结构模型和引入全局寻优能力更强的智能优化算法以提高双向旋转槽干气密封的稳态密封性能。在综合分析国内外干气密封典型双向旋转槽结构特点的基础上，提出一种动压槽倾角可变的双向旋转槽统一模型。建立双向旋转槽干气密封的几何模型和数学模型，采用有限差分法求解端面膜压控制方程，获得开启力和气膜刚度等稳态性能参数。分析了动压槽倾斜角对干气密封稳态性能的影响规律，对比分析了不同速度条件下单因素优化、迭代优化和遗传算法优化等三种优化方法对提高双向旋转槽干气密封稳态性能的作用。结果表明：相较于以往双向树形槽干气密封单因素优化的结果，基于遗传算法的统一模型槽干气密封获得的开启力和气膜刚度显著提高，最大增幅分别达到6%和55%；在高速条件下，上游动压槽螺旋角为锐角，下游动压槽螺旋角为钝角的似机翼形双向旋转槽干气密封具有最大的开启力和气膜刚度。     

基于Kriging模型与遗传算法结合的RHCM成型工艺参数优化

为了提高高光无痕注塑成型(rapid heat cycle molding,RHCM)制品综合品质,提出了一种基于Kriging模型与遗传算法(genetic algorithm,GA)结合的工艺参数优化策略.将该策略应用于某空调柜机出风面板成型,以正交实验法规划实验,通过CAE分析获取实验样本数据,借助数据归一化法、线性加权法、直观分析法等数据处理方法,得到了对RHCM成型影响显著的工艺参数依次为保压时间、冷却时间、熔体温度、加热时间.然后引入Kriging建模理论,建立了RHCM成型制品综合品质与主要成型工艺参数的近似模型,采用GA对建立的近似模型在可行解空间搜寻最优解.得到的最优工艺参数为:加热时间36.9 s,熔体温度182.9℃,保压压力88.5 MPa,冷却时间51.3 s.最后,通过CAE分析和生产试制分别验证了该优化策略的可行性和合理性.