【摘要】：產(chǎn)品色彩意象通過情感認知傳達消費者的色彩需求,為探討用戶的色彩意象與色彩需求間的內(nèi)在關(guān)聯(lián),準確把握消費群體對產(chǎn)品色彩的情感意象,將多用戶色彩意象作為決策因素,提出一個基于混合智能方法的色彩決策系統(tǒng).該系統(tǒng)采用自適應(yīng)策略調(diào)整慣性權(quán)重和混沌序列產(chǎn)生學習因子,提出粒子群改進算法;將改進的粒子群算法用于優(yōu)化徑向基人工神經(jīng)網(wǎng)絡(luò),并建立預測模型;通過模型預測得到各用戶的需求色彩;利用模糊C-均值聚類方法從需求色彩中提取用于產(chǎn)品設(shè)計的決策色彩.通過汽車外飾色彩的測試與評估結(jié)果表明,文中建立的色彩預測模型性能卓越,決策的色彩用戶滿意度較好,可設(shè)計出符合消費者真實意象需求的色彩方案,并為各類產(chǎn)品色彩的設(shè)計提供理論指導.
[Abstract]:The product color image conveys the consumer's color demand through the emotion cognition, in order to probe into the inherent relation between the user's color image and the color demand, the consumer group's emotion image to the product color is accurately grasped. A color decision system based on hybrid intelligent method is proposed, which takes multi-user color image as decision factor. The adaptive strategy is used to adjust the inertia weight and the learning factor of chaotic sequence, and an improved particle swarm optimization algorithm is proposed, which is used to optimize the radial basis function artificial neural network and establish the prediction model. The demand color of each user is obtained by model prediction, and the decision color for product design is extracted from the demand color by fuzzy C- mean clustering method. The test and evaluation results of automobile exterior decoration color show that the color prediction model established in this paper has excellent performance and the color user satisfaction of decision making is better, and the color scheme can be designed to meet the needs of consumers' real image. And for all kinds of product color design to provide theoretical guidance.
【作者單位】： 贛南師范大學物理與電子信息學院;南昌大學機電工程學院;南京林業(yè)大學信息科學技術(shù)學院;
【基金】：國家自然科學基金(51663001,51463015,51377025) 江西省教育廳科學技術(shù)研究項目(GJJ151012,GJJ150983)
【分類號】：TB472

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