机械工程学报 ›› 2026, Vol. 62 ›› Issue (9): 291-310.doi: 10.3901/JME.260422
• 数字化设计与制造 • 上一篇
丁满1, 俱一娴1, 刘政文1, 白仲航1,2
收稿日期:2025-06-03
修回日期:2025-11-26
发布日期:2026-07-08
作者简介:丁满,女,1979 年出生,博士,教授,博士研究生导师。主要研究方向为智能设计、产品色彩情感设计。E-mail:dingman@hebut.edu.cn ;俱一娴,女,2000年出生,硕士研究生。主要研究方向为产品情感化智能设计。E-mail:2904731767@qq.com;刘政文,男,2001年出生,硕士研究生。主要研究方向为智能设计。E-mail:a5054132976@163.com;白仲航(通信作者),男,1978 年出生,博士后,教授,博士研究生导师。主要研究方向为创新设计、功能设计。E-mail:baizhonghang@hebut.edu.cn
基金资助:DING Man1, JU Yixian1, LIU Zhengwen1, BAI Zhonghang1,2
Received:2025-06-03
Revised:2025-11-26
Published:2026-07-08
摘要: 随着人工智能技术的渗透及人类情感需求满足阈限的提高,产品情感化智能设计领域内的不确定性因素愈加凸显且深度耦合日益增强,引发了用户情感需求与产品特征错位、产品最终方案失效及废弃等一系列问题。近年来,针对产品情感化智能设计中不确定性问题的探究涌现了大量研究成果,为完整、系统总结及讨论当前产品情感化智能设计领域内面向不确定性的相关研究,首先介绍产品情感化智能设计的研究体系及内容,然后按照研究体系系统梳理其存在的不确定性问题,并从面向不确定性的用户情感信息的智能挖掘、用户情感与产品特征关联的智能建立、产品方案的智能生成、产品方案的智能评价四个方面,分析其研究内容及关键技术。最后,结合目前的技术发展及研究不足,对未来趋势进行展望,以期实现产品情感化智能设计不确定性问题研究的系统化梳理与总结,推动后续理论及实践研究的进一步形成与发展。
中图分类号:
丁满, 俱一娴, 刘政文, 白仲航. 面向不确定性的产品情感化智能设计研究综述与展望[J]. 机械工程学报, 2026, 62(9): 291-310.
DING Man, JU Yixian, LIU Zhengwen, BAI Zhonghang. A Review and Prospects of Research on Intelligent Product Emotional Design for Uncertainty[J]. Journal of Mechanical Engineering, 2026, 62(9): 291-310.
| [1] 薛塬,臧冀原,孔德婧,等. 面向智能制造的产业模式演变与创新应用[J]. 机械工程学报,2022,58(18):303-318. XUE Yuan,ZANG Jiyuan,KONG Dejing,et al. Evolution and innovative implementation of industrial model for intelligent manufacturing[J]. Journal of Mechanical Engineering,2022,58(18):303-318. [2] 张党,赵永宣,王振军,等. 数据-知识混合驱动的离散制造系统智能控制体系构架研究[J]. 机械工程学报,2024,60(6):1-10,20. ZHANG Dang,ZHAO Yongxuan,WANG Zhenjun,et al. Research on data-knowledge hybrid-driven intelligent control system architecture for discrete manufacturing systems[J]. Journal of Mechanical Engineering,2024,60(6):1-10,20. [3] FUNG C K Y,KWONG C K,CHAN K Y,et al. A guided search genetic algorithm using mined rules for optimal affective product design[J]. Engineering Optimization,2014,46(8):1094-1108. [4] KAKLAUSKAS A,JOKUBAUSKAS D,CERKAUSKAS J,et al. Affective analytics of demonstration sites[J]. Engineering Applications of Artificial Intelligence,2019,81:346-372. [5] 冯毅雄,娄山河,王绪鹏,等. 面向性能的定制产品感性意象评价方法研究[J]. 机械工程学报,2020,56(9):181-190. FENG Yixiong,LOU Shanhe,WANG Xupeng,et al. Research on performance-oriented evaluation method for perceptual imagery of customised products[J]. Journal of Mechanical Engineering,2020,56(9):181-190. [6] ZHAO Q,WU P,LIAN J,et al. TaneNet:Two-level attention network based on emojis for sentiment analysis[J]. IEEE Access,2024,12:86106-86119. [7] AERTS D,GABORA L,SOZZO S. Concepts and their dynamics:A quantum-theoretic modeling of human thought[J]. Topics in Cognitive Science,2013,5(4):737-772. [8] WANG Y,SONG W,TAO W,et al. A systematic review on affective computing:Emotion models,databases,and recent advances[J]. Information Fusion,2022,83:19-52. [9] 刘晓明,李丞正旭,吴少聪,等. 文本分类算法及其应用场景研究综述[J]. 计算机学报,2024,47(6):1244-1287. LIU Xiaoming,LI Chengzhengxu,WU Shaocong,et al. A research review of text categorization algorithms and their application scenarios[J]. Chinese Journal of Computers,2024,47(6):1244-1287. [10] LASSO S,KREYE M,DAALHUIZEN J,et al. Exploring the link between uncertainty and project activities in new product development[J]. Journal of Engineering Design,2020,31(11-12):531-551. [11] 林丽,郭主恩,阳明庆. 情感化智能设计研究现状及发展趋势[J]. 包装工程,2023,44(16):22-31. LIN Li,GUO Zhuen,YANG Mingqing. Research status and development trend of emotional intelligent design[J]. Packaging Engineering,2023,44(16):22-31. [12] QU L. Influence of emotional factors (positive,negative) on the usefulness of product reviews based on big data[J]. Wireless Communications and Mobile Computing,2022,2022(1):2958718. [13] 王友卫,刘瑞,凤丽洲. 基于用户性格和语义-结构特征的文本评论情感分类方法[J]. 电子学报,2024,52(5):1657-1669. WANG Youwei,LIU Rui,FENG Lizhou. A sentiment classification method for text comments based on user personality and semantic-structural features[J]. Acta Electronica Sinica,2024,52(5):1657-1669. [14] BALTERS S,STEINERT M. Capturing emotion reactivity through physiology measurement as a foundation for affective engineering in engineering design science and engineering practices[J]. Journal of Intelligent Manufacturing,2017,28:1585-1607. [15] SHU T,WANG Z,LIN L,et al. Customer perceived risk measurement with NLP method in electric vehicles consumption market:Empirical study from China[J]. Energies,2022,15(5):1637. [16] DING M,ZHAO L,SUN M,et al. An ISM-BN-GA based methodology for product emotional design[J]. Displays,2022,74:102279. [17] 罗仕鉴,龚何波,林伟. 智能产品交互设计研究现状与进展[J]. 机械工程学报,2023,59(11):1-15. LUO Shijian,GONG Hebo,LIN Wei. Research status and progress of interaction design for intelligent products[J]. Journal of Mechanical Engineering,2023,59(11):1-15. [18] 李雄,苏建宁,张志鹏. 基于深度学习的产品概念草图生成设计研究[J]. 机械工程学报,2023,59(11):16-30. LI Xiong,SU Jianning,ZHANG Zhipeng. Research on design of product concept sketch generation based on deep learning[J]. Journal of Mechanical Engineering,2023,59(11):16-30. [19] WANG T. A novel approach of integrating natural language processing techniques with fuzzy TOPSIS for product evaluation[J]. Symmetry,2022,14(1):120. [20] ZUO Y,WANG Z. Subjective product evaluation system based on Kansei Engineering and analytic hierarchy process[J]. Symmetry,2020,12(8):1340. [21] CHAN K Y,ENGELKE U. Varying spread fuzzy regression for affective quality estimation[J]. IEEE Transactions on Fuzzy Systems,2016,25(3):594-613. [22] 莫振冲,宫琳,叶帆,等. 基于知识图谱的模糊前端需求结构解生成方法[J]. 计算机集成制造系统,2022,28(9):2683-2699. MO Zhenchong,GONG Lin,YE Fan,et al. A fuzzy front-end demand structure solution generation method based on knowledge graph[J]. Computer Integrated Manufacturing Systems,2022,28(9):2683-2699. [23] 洪兆溪,冯毅雄,娄山河,等. 复杂产品不确定性智能设计研究综述与展望[J]. 机械工程学报,2023,59(19):213-236. HONG Zhaoxi,FENG Yixiong,LOU Shanhe,et al. Review and prospect of intelligent design research on uncertainty of complex products[J]. Journal of Mechanical Engineering,2023,59(19):213-236. [24] EREM B,MARTINEZ ORELLANA R,HYDE D E,et al. Extensions to a manifold learning framework for time-series analysis on dynamic manifolds in bioelectric signals[J]. Physical Review E,2016,93(4):042218. [25] 纪雪,高琦,李先飞,等. 考虑产品属性层次性的评论挖掘及需求获取方法[J]. 计算机集成制造系统,2020,26(3):747-759. JI Xue,GAO Qi,LI Xianfei,et al. Review mining and requirement acquisition method considering product attribute hierarchy[J]. Computer Integrated Manufacturing Systems,2020,26(3):747-759. [26] NG C Y,LAW K M Y. Investigating consumer preferences on product designs by analyzing opinions from social networks using evidential reasoning[J]. Computers & Industrial Engineering,2020,139:106180. [27] 成方敏,余隋怀,初建杰,等. 大规模用户语义描述需求建模与分析[J]. 计算机集成制造系统,2022,28(2):601-611. CHENG Fangmin,YU Suihuai,CHU Jianjie,et al. Modelling and analysis of large-scale user semantic description requirements[J]. Computer Integrated Manufacturing Systems,2022,28(2):601-611. [28] 张书涛,杨志强,苏建宁,等. 用户评论异质情感的主题聚类仿真[J]. 控制与决策,2024,39(11):3645-3654. ZHANG Shutao,YANG Zhiqiang,SU Jianning,et al. Topic clustering simulation for heterogeneous sentiment of user reviews[J]. Control and Decision,2024,39(11):3645-3654. [29] FOULADFAR F,DEHKORDI M N,BASIRI M E. Predicting the helpfulness score of product reviews using an evidential score fusion method[J]. IEEE Access,2020,8:82662-82687. [30] 胡炳涛,冯毅雄,刘继红,等. 面向“互联网+”定制产品的智能适应性设计研究[J]. 机械工程学报,2023,59(12):109-125. HU Bingtao,FENG Yixiong,LIU Jihong,et al. Research on intelligent adaptive design for ‘Internet+’ customised products[J]. Journal of Mechanical Engineering,2023,59(12):109-125. [31] YANG C M,DENG W. User-satisfaction framework for the development of shoes for the elderly in fuzzy environment[J]. Alexandria Engineering Journal,2023,63:427-440. [32] 任丽,林丽,阳明庆,等. 脑视觉认知机制下意象-产品归类的集群用户偏好推理[J]. 机械工程学报,2023,59(15):282-292. REN Li,LIN Li,YANG Mingqing,et al. Clustered user preference inference for imagery-product categorisation under brain visual cognitive mechanism[J]. Journal of Mechanical Engineering,2023,59(15):282-292. [33] 郭主恩,林丽,阳明庆,等. 基于无意识多模态内隐测量的产品意象提取模型构建[J]. 计算机集成制造系统,2022,28(4):1150-1163. GUO Zhuen,LIN Li,YANG Mingqing,et al. Construction of product imagery extraction model based on unconscious multimodal implicit measurement[J]. Computer Integrated Manufacturing Systems,2022,28(4):1150-1163. [34] 杨晓楠,王帅,牛红伟,等. 眼动交互关键技术研究现状与展望[J]. 计算机集成制造系统,2024,30(5):1595-1609. YANG Xiaonan,WANG Shuai,NIU Hongwei,et al. Research status and prospect of key technologies of eye movement interaction[J]. Computer Integrated Manufacturing Systems,2024,30(5):1595-1609. [35] LI H,YAN J. Does visual review content enhance review helpfulness? A text-mining approach[J]. IEEE Access,2024,12:27633-27647. [36] NAWAZ R,CHEAH K H,NISAR H,et al. Comparison of different feature extraction methods for EEG-based emotion recognition[J]. Biocybernetics and Biomedical Engineering,2020,40(3):910-926. [37] ZHANG M,SUN L,WANG G A,et al. Using neutral sentiment reviews to improve customer requirement identification and product design strategies[J]. International Journal of Production Economics,2022,254:108641. [38] ZENG H,ZHANG J,ZAKARIA W,et al. InstanceEasyTL:An improved transfer-learning method for EEG-based cross-subject fatigue detection[J]. Sensors,2020,20(24):7251. [39] PANDEY P,SEEJA K R. Subject independent emotion recognition from EEG using VMD and deep learning[J]. Journal of King Saud University-Computer and Information Sciences,2022,34(5):1730-1738. [40] SONG T,LIU S,ZHENG W,et al. Variational instance-adaptive graph for EEG emotion recognition[J]. IEEE Transactions on Affective Computing,2021,14(1):343-356. [41] WANG F,WU S,ZHANG W,et al. Emotion recognition with convolutional neural network and EEG-based EFDMs[J]. Neuropsychologia,2020,146:107506. [42] 郑伟龙,石振锋,吕宝粮. 用异质迁移学习构建跨被试脑电情感模型[J]. 计算机学报,2020,43(2):177-189. ZHENG Weilong,SHI Zhenfeng,LÜ Baoliang. Constructing cross-subject EEG emotion models with heterogeneous transfer learning[J]. Chinese Journal of Computers,2020,43(2):177-189. [43] ZHANG X,WANG S,XU K,et al. Cross-subject EEG-based emotion recognition through dynamic optimization of random forest with sparrow search algorithm[J]. Mathematical Biosciences and Engineering,2024,21(3):4779-4800. [44] 耿秀丽,薄振一. 基于网络博弈的顾客需求权重确定方法[J]. 计算机集成制造系统,2020,26(10):2792-2798. GENG Xiuli,BO Zhenyi. A method for determining customer demand weights based on network games[J]. Computer Integrated Manufacturing Systems,2020,26(10):2792-2798. [45] JIANG H,KWONG C K,PARK W Y. Probabilistic fuzzy regression approach for preference modeling[J]. Engineering Applications of Artificial Intelligence,2017,64:286-294. [46] 丁满,孙鸣宇,张新新,等. 基于知识超图的产品色彩情感设计[J]. 机械工程学报,2024,60(17):339-348. DING Man,SUN Mingyu,ZHANG Xinxin,et al. Product color emotional design based on knowledge hypergraph[J]. Journal of Mechanical Engineering,2024,60(17):339-348. [47] PEI H,LIU X,HUANG X,et al. A personalized recommendation method under the cloud platform based on users’ long-term preferences and instant interests[J]. Advanced Engineering Informatics,2022,54:101763. [48] JIANG H,GUO G,SABETZADEH F,et al. Model variational consumer preferences based on online reviews using sentiment analysis and PSO-based DENFIS approaches[J]. Journal of Intelligent & Fuzzy Systems,2022,43(3):2407-2418. [49] 丁满,丁婷婷,宋美佳,等. 基于内隐测量和BP神经网络的产品色彩情感化设计[J]. 计算机集成制造系统,2023,29(2):616-627. DING Man,DING Tingting,SONG Meijia,et al. Emotional design of product color based on implicit measurement and BP neural network[J]. Computer Integrated Manufacturing Systems,2023,29(2):616-627. [50] 苏珂,李大帅,张伟. 产品设计中用户潜在需求获取方法研究综述[J]. 计算机集成制造系统,2023,29(4):1284-1300. SU Ke,LI Dashuai,ZHANG Wei. A review of research on methods for acquiring users' potential needs in product design[J]. Computer Integrated Manufacturing Systems,2023,29(4):1284-1300. [51] DING M,QIN H,ZHANG X,et al. Designing the color of electric motorcycle products emotionally based on the dynamic field theory and deep learning[J]. Displays,2024,81:102584. [52] 林丽,任丽,阳明庆. 基于改进加权协同过滤的集群用户黑箱个性意象预测[J]. 浙江大学学报,2022,56(4):803-808. LIN Li,REN Li,YANG Mingqing. Black-box personality imagery prediction for cluster users based on improved weighted collaborative filtering[J]. Journal of Zhejiang University,2022,56(4):803-808. [53] JEONG J. Identifying consumer preferences from user-generated content on Amazon. com by leveraging machine learning[J]. IEEE Access,2021,9:147357-147396. [54] 高子建,张晗睿,窦万春,等. 基于谱聚类和隐语义模型的智能协同推荐方法[J]. 计算机集成制造系统,2021,27(9):2517-2524. GAO Zijian,ZHANG Hanrui,DOU Wanchun,et al. Intelligent collaborative recommendation method based on spectral clustering and hidden semantic model[J]. Computer Integrated Manufacturing Systems,2021,27(9):2517-2524. [55] 王友卫,刘奥,凤丽洲. 基于知识蒸馏和评论时间的文本情感分类新方法[J]. 吉林大学学报,2025,55(5):1664-1674. WANG Youwei,LIU Ao,FENG Lizhou. A new method for text sentiment classification based on knowledge distillation and comment time[J]. Journal of Jilin University,2025,55(5):1664-1674. [56] 张舒涵,牟宇锋,李存波,等. 基于脑电网络的情绪识别研究进展[J]. 电子科技大学学报,2024,53(5):771-784. ZHANG Shuhan,MU Yufeng,LI Cunbo,et al. Research progress of emotion recognition based on EEG network[J]. Journal of University of Electronic Science and Technology of China,2024,53(5):771-784. [57] 周逸凡,张灵维,周正东,等. 基于注意力机制和深度学习的群体语言想象脑电信号分类[J]. 浙江大学学报,2024,58(12):2540-2546. ZHOU Yifan,ZHANG Lingwei,ZHOU Zhengdong,et al. Classification of group speech imagined EEG signals based on attention mechanism and deep learning[J]. Journal of Zhejiang University,2024,58(12):2540-2546. [58] LOPES F,LEAL A,MEDEIROS J,et al. Automatic electroencephalogram artifact removal using deep convolutional neural networks[J]. IEEE Access,2021,9:149955-149970. [59] 丁满,孙鸣宇,冯光宇. 技术视阈下产品色彩情感设计研究综述与展望[J]. 包装工程,2023,44(16):10-21,509. DING Man,SUN Mingyu,FENG Guangyu. Review and prospect of product colour emotion design research under the technological perspective[J]. Packaging Engineering,2023,44(16):10-21,509. [60] SHAO H,PAN S,SONG Y,et al. Research on product conceptual design scheme configurations from a designer-user conflict perspective[J]. Applied Sciences,2024,14(7):2968. [61] KANG X,YANG M,WU Y,et al. Integrating evaluation grid method and fuzzy quality function deployment to new product development[J]. Mathematical Problems in Engineering,2018,2018(1):2451470. [62] CHENG Y,LI Y,ZHANG N,et al. A knowledge graph-enabled multi-domain mapping approach supporting product rapid design:A case study of new energy vehicles[J]. Advanced Engineering Informatics,2024,62:102779. [63] 张雷,钟言久,袁远,等. 基于数据挖掘的绿色设计中客户需求向工程特性权重转化方法[J]. 中国机械工程,2019,30(2):174-182. ZHANG Lei,ZHONG Yanjiu,YUAN Yuan,et al. A data mining-based method for transforming customer requirements to engineering characteristic weights in green design[J]. China Mechanical Engineering,2019,30(2):174-182. [64] 胡东方,李奕辰,李彦兵. 基于卡诺和人工免疫系统的顾客需求产品设计[J]. 计算机集成制造系统,2018,24(10):2536-2546. HU Dongfang,LI Yichen,LI Yanbing. Customer demand product design based on Kano and artificial immune system[J]. Computer Integrated Manufacturing Systems,2018,24(10):2536-2546. [65] 杨程,陈辰,唐智川. 基于脑电的产品意象推理模型研究[J]. 机械工程学报,2018,54(23):126-136. YANG Cheng,CHEN Chen,TANG Zhichuan. Research on product imagery reasoning model based on EEG[J]. Journal of Mechanical Engineering,2018,54(23):126-136. [66] XU X,DOU Y,OUYANG W,et al. A product requirement influence analysis method based on multilayer dynamic heterogeneous networks[J]. Advanced Engineering Informatics,2024,59:102352. [67] 王世杰,苏建宁,张书涛,等. 面向多维属性特征的关键需求信息识别[J]. 计算机集成制造系统,2025,31(6):1978-1990. WANG Shijie,SU Jianning,ZHANG Shutao,et al. Multidimensional attribute feature oriented critical requirement information identification[J]. Computer Integrated Manufacturing Systems,2025,31(6):1978-1990. [68] WANG T,YANG L. Combining GRA with a fuzzy QFD model for the new product design and development of Wickerwork Lamps[J]. Sustainability,2023,15(5):4208. [69] 陈亮,李廖平. 基于混合博弈的产品多学科柔性设计决策[J]. 中国机械工程,2017,28(15):1854-1861. CHEN Liang,LI Liaoping. Multidisciplinary flexible design decision-making for products based on hybrid games[J]. China Mechanical Engineering,2017,28(15):1854-1861. [70] WANG P. Product modeling design method based on graph neural network and fuzzy inference theory[J]. Alexandria Engineering Journal,2023,77:513-524. [71] XIAO X,ZHENG X. A dynamic network resource demand predicting algorithm based on incremental design of RBF[J]. Procedia Computer Science,2019,147:29-35. [72] WEI W,JI J,WUEST T,et al. Product family flexible design method based on dynamic requirements uncertainty analysis[J]. Procedia CIRP,2017,60:332-337. [73] WANG Z,CHEN C H,LI X,et al. A context-aware concept evaluation approach based on user experiences for smart product-service systems design iteration[J]. Advanced Engineering Informatics,2021,50:101394. [74] 邱若臻,肖欣,孙艺萌,等. 不确定环境下的鲁棒多产品、多周期供应链网络设计模型[J]. 计算机集成制造系统,2019,25(10):2655-2665. QIU Ruozhen,XIAO Xin,SUN Yimeng,et al. Robust multi-product,multi-cycle supply chain network design model under uncertain environment[J]. Computer Integrated Manufacturing Systems,2019,25(10):2655-2665. [75] 朱上上,楼晓霏,李文杰,等. 基于可拓设计的产品个性化定制方法[J]. 计算机集成制造系统,2020,26(10):2661-2669. ZHU Shangshang,LOU Xiaofei,LI Wenjie,et al. A product personalisation approach based on extenics design[J]. Computer Integrated Manufacturing Systems,2020,26(10):2661-2669. [76] 娄山河,冯毅雄,胡炳涛,等. 人机认知协同的复杂装备概念设计:挑战、进展和展望[J]. 机械工程学报,2024,60(11):2-19. LOU Shanhe,FENG Yixiong,HU Bingtao,et al. Conceptual design of complex equipment based on human-machine cognitive collaboration:challenges,progress and prospects[J]. Journal of Mechanical Engineering,2024,60(11):2-19. [77] 孙之琳,王凯峰,顾佩华. 设计理论与方法研究的回顾与展望[J]. 机械工程学报,2024,60(13):2-20. SUN Zhilin,WANG Kaifeng,GU Peihua. Review and prospect of design theory and methodology research[J]. Journal of Mechanical Engineering,2024,60(13):2-20. [78] Kuegler P,Dworschak F,Schleich B,et al. The evolution of knowledge-based engineering from a design research perspective:Literature review 2012–2021[J]. Advanced Engineering Informatics,2023,55:101892. [79] GUNPINAR E,KHAN S. A multi-criteria based selection method using non-dominated sorting for genetic algorithm based design[J]. Optimization and Engineering,2020,21(4):1319-1357. [80] ZHANG J,CAO G,PENG Q,et al. A time correlation based clustering method for a design of a transformable product[J]. Applied Sciences,2020,10(1):406. [81] DING M,DONG W. Multiemotional product color design using gray theory and nondominated sorting genetic algorithm-III[J]. Color Research & Application,2020,45(1):142-155. [82] 罗仕鉴,崔志彤,帅俊成,等. 基于群智协同计算的高速列车概念生成设计研究[J]. 机械工程学报,2023,59(11):65-73. LUO Shijian,CUI Zhitong,SHUAI Juncheng,et al. Research on concept generation design of high-speed train based on groupwise collaborative computation[J]. Journal of Mechanical Engineering,2023,59(11):65-73. [83] 王阳,裘乐淼,刘晓健,等. 基于关联约束网络的定制产品隐式需求激活技术[J]. 计算机集成制造系统,2020,26(7):1855-1867. WANG Yang,QIU Lemiao,LIU Xiaojian,et al. Implicit demand activation technology for customised products based on associative constraint networks[J]. Computer Integrated Manufacturing Systems,2020,26(7):1855-1867. [84] 从靖晨,项忠霞,李心雨,等. 基于知识图谱的智能产品服务系统交互设计研究[J]. 机械工程学报,2023,59(11):94-105. CONG Jingchen,XIANG Zhongxia,LI Xinyu,et al. Research on the interaction design of intelligent product service system based on knowledge graph[J]. Journal of Mechanical Engineering,2023,59(11):94-105. [85] 吴俊杰,刘冠男,王静远,等. 数据智能:趋势与挑战[J]. 系统工程理论与实践,2020,40(8):2116-2149. WU Junjie,LIU Guannan,WANG Jingyuan,et al. Data intelligence:trends and challenges[J]. Systems Engineering Theory and Practice,2020,40(8):2116-2149. [86] HU X,LIU A,DAI Y. Combining ChatGPT and knowledge graph for explainable machine learning-driven design:a case study[J]. Journal of Engineering Design,2024:1-23. [87] 王愫,刘月林,孙利. 面向AI生成的产品概念设计方案智能评估方法[J]. 计算机集成制造系统,2025,31(1):20-34. WANG Su,LIU Yuelin,SUN Li. An intelligent evaluation method for AI-generated product conceptual design solutions[J]. Computer Integrated Manufacturing Systems,2025,31(1):20-34. [88] BALLOCCU G,BORATTO L,FENU G,et al. Reinforcement recommendation reasoning through knowledge graphs for explanation path quality[J]. Knowledge-Based Systems,2023,260:110098. [89] SCHNEIDER M,GREIFZU N,WANG L,et al. An end-to-end machine learning approach with explanation for time series with varying lengths[J]. Neural Computing and Applications,2024,36(13):7491-7508. [90] GUO X,LIU Y,ZHAO W,et al. Supporting resilient conceptual design using functional decomposition and conflict resolution[J]. Advanced Engineering Informatics,2021,48:101262. [91] 郭鑫,王海涵,王杰,等. 韧性产品交互式概念设计与知识推理方法研究[J]. 机械工程学报,2023,59(11):74-83. GUO Xin,WANG Haihan,WANG Jie,et al. Research on interactive conceptual design and knowledge reasoning method for resilient products[J]. Journal of Mechanical Engineering,2023,59(11):74-83. [92] SUN H,GUO W,SHAO H,et al. Dynamical mining of ever-changing user requirements:A product design and improvement perspective[J]. Advanced Engineering Informatics,2020,46:101174. [93] HUANG Z,GUO X,LIU Y,et al. A smart conflict resolution model using multi-layer knowledge graph for conceptual design[J]. Advanced Engineering Informatics,2023,55:101887. [94] 苏建宁,彭正杰,邱凯,等. 基于信息熵和最小偏差的产品意象评价方法[J]. 机械设计,2022,39(4):129-134. SU Jianning,PENG Zhengjie,QIU Kai,et al. A product imagery evaluation method based on information entropy and minimum deviation[J]. Mechanical Design,2022,39(4):129-134. [95] 杨延璞,安为岚,杨沁夏,等. 工业设计方案决策的异构信息融合方法[J]. 西北工业大学学报,2022,40(5):1133-1144. YANG Yanpu,AN Weilan,YANG Qinxia,et al. A heterogeneous information fusion method for industrial design solution decision-making[J]. Journal of Northwestern Polytechnical University,2022,40(5):1133-1144. [96] WANG Y M,PAN X H,HE S F,et al. A new decision-making framework for site selection of electric vehicle charging station with heterogeneous information and multigranular linguistic terms[J]. IEEE Transactions on Fuzzy Systems,2022,31(2):485-499. [97] 裴卉宁,刘鑫宇,李文华,等. 面向冷启动用户的云平台服务决策推荐方法[J]. 计算机集成制造系统,2025,31(3):1024-1037. PEI Huining,LIU Xinyu,LI Wenhua,et al. A decision recommendation method for cloud platform services for cold-start users[J]. Computer Integrated Manufacturing Systems,2025,31(3):1024-1037. [98] SUN M,GENG Y,ZHAO J. Multi-Attribute group decision-making methods based on entropy weights with q-Rung picture uncertain linguistic fuzzy information[J]. Symmetry,2023,15(11):2027. [99] ALCANTUD J C R,SANTOS-GARCÍA G. A new criterion for soft set based decision making problems under incomplete information[J]. International Journal of Computational Intelligence Systems,2017,10(1):394-404. [100] WU P,LI H,MERIGO J M,et al. Integer programming modeling on group decision making with incomplete hesitant fuzzy linguistic preference relations[J]. IEEE Access,2019,7:136867-136881. [101] 罗党,张慧慧,孙德才. 考虑决策者心理行为的灰色多属性群体决策方法[J]. 控制与决策,2021,36(7):1779-1785. LUO Dang,ZHANG Huihui,SUN Decai. A grey multi- attribute group decision-making method considering psychological behaviour of decision makers[J]. Control and Decision,2021,36(7):1779-1785. [102] SAGHARI A,BUDINSKÁ I,HOSSEINIMEHR M,et al. A robust-reliable decision-making methodology based on a combination of stakeholders’ preferences simulation and kdd techniques for selecting automotive platform benchmark[J]. Symmetry,2023,15(3):750. [103] LOU S,FENG Y,LI Z,et al. An edge-based distributed decision-making method for product design scheme evaluation[J]. IEEE Transactions on Industrial Informatics,2020,17(2):1375-1385. [104] GENG B,BRAHMA S,WIMALAJEEWA T,et al. Prospect theoretic utility based human decision making in multi-agent systems[J]. IEEE Transactions on Signal Processing,2020,68:1091-1104. [105] LEI W,MA W,LI X,et al. Three-way group decision based on regret theory under dual hesitant fuzzy environment:An application in water supply alternatives selection[J]. Expert Systems with Applications,2024,237:121249. [106] 苏兆婧,余隋怀,初建杰,等. 面向云服务平台的产品感性评价及标注模型[J]. 计算机集成制造系统,2021,27(3):868-877. SU Zhaojing,YU Suihuai,CHU Jianjie,et al. A product perceptual evaluation and labelling model for cloud service platform[J]. Computer Integrated Manufacturing Systems,2021,27(3):868-877. [107] 彭张林,杜一甫,程啸先,等. 面向设计众包的产品概念方案评价与选择[J]. 计算机集成制造系统,2023,29(10):3450-3461. PENG Zhanglin,DU Yifu,CHENG Xiaoxian,et al. Evaluation and selection of product concept scheme for design crowdsourcing[J]. Computer Integrated Manufacturing Systems,2023,29(10):3450-3461. [108] 安相华,牛春亮,薛冬娟,等. 基于变粒度权重与群决策的产品服务系统方案优选方法[J]. 计算机集成制造系统,2016,22(1):155-165. AN Xianghua,NIU Chunliang,XUE Dongjuan,et al. A solution selection method for product service system based on variable granularity weight and group decision making[J]. Computer Integrated Manufacturing Systems,2016,22(1):155-165. [109] WANG X,ZHANG L. A combined weighting model based on maximizing deviation for multiple attribute decision-making[J]. Advances in Materials Science and Engineering,2022,2022(1):7679851. [110] WANG Z,ZHONG Y,CHAI S,et al. Product design evaluation based on improved CRITIC and Comprehensive Cloud-TOPSIS–Applied to automotive styling design evaluation[J]. Advanced Engineering Informatics,2024,60:102361. [111] SUN Y,CAI Y. A flexible decision-making method for green supplier selection integrating TOPSIS and GRA under the single-valued neutrosophic environment[J]. IEEE Access,2021,9:83025-83040. [112] 丛东升,尚建忠,张瑞军,等. 考虑混合不确定性信息的产品多属性方案评价[J]. 系统工程理论与实践,2018,38(9):2409-2415. CONG Dongsheng,SHANG Jianzhong,ZHANG Ruijun,et al. Product multi-attribute programme evaluation considering mixed uncertainty information[J]. Systems Engineering Theory and Practice,2018,38(9):2409-2415. [113] 陈东萍,褚学宁,冯涛,等. 混合不确定条件下基于信息公理的产品服务系统方案评价[J]. 计算机集成制造系统,2014,20(8):2071-2078. CHEN Dongping,CHU Xuening,FENG Tao,et al. Information axiom-based programme evaluation of product-service systems under mixed uncertainty[J]. Computer Integrated Manufacturing Systems,2014,20(8):2071-2078. [114] JOHNEN A K,HARRISON N R. Level of uncertainty about the affective nature of a pictorial stimulus influences anticipatory neural processes:An event- related potential (ERP) study[J]. Neuropsychologia,2020,146:107525. [115] DING M,SUN M,LUO S. Product color emotional design based on 3D knowledge graph[J]. Displays,2024,81:102622. [116] 黄悦欣,余隋怀,初建杰,等. 基于联合学习的概念设计知识抽取与图谱构建[J]. 计算机集成制造系统,2023,29(7):2313-2326. HUANG Yuexin,YU Suihuai,CHU Jianjie,et al. Conceptual design knowledge extraction and graph construction based on joint learning[J]. Computer Integrated Manufacturing Systems,2023,29(7):2313-2326. [117] 耿杰,刘春丽,魏雪梅,等. 基于用户重购行为的产品推荐方法[J]. 计算机研究与发展,2023,60(8):1795-1807. GENG Jie,LIU Chunli,WEI Xuemei,et al. A product recommendation method based on user repurchase behaviour[J]. Computer Research and Development,2023,60(8):1795-1807. [118] RAO C,WANG C,HU Z,et al. Gray uncertain linguistic multiattribute group decision making method based on GCC-HCD[J]. IEEE Transactions on Computational Social Systems,2022,10(2):523-537. [119] KAUR G,GARG H. Multi-attribute decision-making based on Bonferroni mean operators under cubic intuitionistic fuzzy set environment[J]. Entropy,2018,20(1):65. |
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