基于意象的产品色彩设计模型与方法研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
随着消费者生活品质的不断提升,产品色彩所引发的情感体验开始逐渐成为普通消费者的追逐目标,对于产品色彩的意象偏好与需求成为消费者决定购买和使用产品的重要因素。由于产品开发始终要围绕市场和消费者的需求,因此,多数企业已将产品色彩意象研究视为其生存竞争的主要工具。而传统方法无法充分体现消费者多样且多变的色彩意象需求的问题,已成为制约产品色彩设计水平的瓶颈。因此,如何准确把握及合理表达消费者对于产品色彩的复杂情感意象需求等成为解决这一难题的关键。为此,论文以消费者对于产品的色彩意象感知为研究对象,面向产品色彩设计的实际应用问题,建立一套能够适应产品特征变化,并切实符合消费者真实意象需求的产品色彩设计方法。具体内容如下:
     1)针对色彩空间分布形式对于消费者色彩意象空间存在影响问题,提出了考虑色彩空间分布的产品色彩意象评价方法。通过深入分析色彩空间分布形式对于消费者色彩意象感知的影响,将色彩空间分布形式引入到产品色彩意象评价模型中;联合分析被用来建构消费者色彩意象感知与各评价属性间的关联,建立了基于色彩空间分布的产品色彩意象评价模型,藉此推论出目标消费者对于未知色彩组合形式所能给予的意象评价值。通过设计实例验证了对于没有确定色彩空间分布形式的一类设计活动,该方法较孟·斯宾瑟美度评价方法更为贴近消费者的主观色彩意象。
     2)针对多工作模式产品存在色彩面积变化问题,提出了多工作模式产品色彩意象评价方法。重点分析存多工作模式产品的配色特征,将色彩面积变化因素考虑到产品色彩意象评价模型中;基于灰色关联分析法建立产品方案色彩与消费者意象之间的关联模型;运用灰色聚类法判断产品各作业模式下的色彩意象评价值;并将各评价值进行综合考虑,建立了多工作模式产品的色彩意象评价模型。设计实例验证了该方法在处理存在色彩面积变化因素的多工作模式产品的色彩设计问题时,较传统评价方法更加贴近消费者的色彩意象感知。
     3)针对消费者对于产品色彩意象很难明确给出期望值问题,提出了产品色彩模糊优化设计方法。针对消费者对于色彩意象表达存在的模糊性、不确定性问题,将决策信息不完全明确情况下的产品色彩设计问题转化为给定解空间的最优解模糊搜索问题,建立了产品色彩设计模糊设计模型,并采用将模糊变量进行离散化的方法产生备选方案解集;采用粒子群算法对该模型进行求解,实现产品色彩方案的快速生成;采用折衷规划的方法获得产品色彩的最佳调和方案。该方法能够改善产品色彩设计阶段所遭遇的不确定问题,提高产生满意解的几率,从而提高产品色彩设计品质。通过设计实例验证了该方法的可行性。
     4)针对消费者对于产品色彩意象的多维性及复杂性,提出了基于多维情感的产品色彩优化设计方法。在对多工作模式产品色彩设计模型扩展的基础上,建立了多维情感产品色彩设计模型;运用因素分析结合普氏分析建立消费者情感需求的多维度空间:采用模糊偏好的方法建立各情感维度间的重要程度关系;采用粒子群算法对多维情感产品色彩设计模型进行求解。该方法能够满足更多消费者的复杂情感意象需求,提高设计成功率,并为解决消费者复杂情感需求问题提供了理论基础。最后通过实例验证了考虑情感准则多维性的重要性以及所提方法的有效性。
As life quality increasingly promotes, emotional experience caused by product color has been becoming the pursuing target of ordinary consumers. The preferences and requirements on product color images become the key factor which determines consumers' purchasing and using behaviors. Product development should be always based on requirements of market and consumers, so most of corporations has considered product color image as a competitive tool. The traditional methods can not completely reflect the various and changeable color image requirements of consumers, which have become the restriction of product color design. Therefore, the key point to solve this problem is to exactly grasp and rationally express consumers'requirements of color image and multi-emotions. For this reason, this paper set consumers'perception on product color image as research object. Aiming at the actual application of product color design, this paper created an intelligent design method which could be adjust to product features and actually satisfy consumer's image requirements. More details are as follows:
     Firstly, for the influence of color layout on consumers'color image space, this paper proposed a product color image evaluation method based on color layout. It made depth analysis about the influence of color layout on consumers'color image. It also introduced the factor of color layout into the product color image evaluation model, which was considered as evaluating attribute together with hue, value and chroma. This paper used Conjoint Analysis to construct the relationship between consumers'color image and each evaluation attribute. On this basis, a product color image evaluation method based on color layout was created, in order to deduce evaluation values of target consumers on unknown color combinations. Especially for the undefined color layout, through a design case this method was proved that it was closer to consumers'subjective images than color harmony aesthetics measure model of MoSpencer.
     Secondly, for the influence of color area changing on consumers' color image space, this paper proposed an integrated color image evaluation method considering color area changing. It focused on the color combining features of multi-working modes products, and introduced color area changing factors into product color image evaluation model. On the basis of gray relational, the correlative model between product color and image was built. Furthermore, gray clustering method was used to determine image evaluating value for color combination. The color combination images for different working modes were all considered as evaluating attributes, to which the corresponding weights were assigned for synthesized evaluation. This method paid attention to both the variability of product with multiple working modes and the indeterminacy of customers' subjective images, and then flexibly and directly evaluated the color combination image for the product with multi-working modes. For the color area changing issue, through a design case, it was proved that this method was closer to the subjective image of customers than single-attribute evaluating approach.
     In addition, for consumers may difficult to provide specific expectation values on product color image, this paper proposed a product color fuzzy design method. Considering the fuzziness and uncertainty of consumers'color image expression, this method transformd product color design with undefined decisions into fuzzy search for optimized solution with given solution space. It constructed product color fuzzy design model, and used fuzzy variables discretization to produce optional scheme solutions. It employed Particle Swarm Optimization to solve the model, and rapidly produced product color schemes. This method is able to improve the uncertainty problem of product color design, increase the generation rate of satisfied solution, and enhance the quality of product color design. Through design case, the feasibility of this method was proved.
     Finally, According to the multidimensionality and complexity of consumers'requirements on product color image, a product color planning method based on multi-emotion was proposed. This method constructed a multi-dimension space of consumers'emotion requirements. On the expansion of multi-working modes product color design model, it constructed a model of multi-emotion product color design, and used factor analysis and Protodyakonov Analysis to create image dimension. It employed Particle Swarm Optimization to find the solution. This method could meet consumers'multi-emotion requirements, improve design success rate, and provide theoretical basis for complex emotion requirements. Through design case, the importance of considering emotion multidimensionality and the validity of the proposed method were proved.
引文
[1]徐江.风格进化驱动的产品创新生成设计技术研究[D].杭州:浙江大学,2008.
    [2]菜淑娟.类神经遗传演算法应用于产品配色系统之建立研究[D].台湾:国立成功大学,2003.
    [3]Jiao J R, Zhang Y, Helander. A Kansei mining system for affective design [J]. Expert Systems with Applications,2006,30(4):658-673.
    [4]萧坤安,产品造型性格意象的认知探讨[D].台湾:国立台湾科技大学,2006.
    [5]驻盈祺.复合式感性意象下产品造型的建构[D].台湾:国立成功大学,2002.
    [6]周君瑞.复合感性意象之塑造-以造型特征为基础[D].台湾:国立成功大学,2001.
    [7]陈建昌.汽车正面造型特征与意象认知之关联性研究[D].台湾:华梵大学,2005.
    [8]张宏睿.设计师和使用者偏好对高尔夫杆头造型意象与认知差异的探讨[D].台湾:国立云林科技大学,2008.
    [9]吴乙鸿.应用类神经遗传演算法建立电脑辅助设计模式之研究[D].台湾:国立成功大学,2000.
    [10]陈姵伊.产品之双色配色意象研究—以行动电话为例[D].台湾:国立台湾科技大学,2003.
    [11]施懿芳.汽车造型轮廓之意象认知与心智分类对应关系研究[D].台湾:国立云林科技大学,2005.
    [12]莊柏宣.形变造型之情感意象预测与探讨[D].台湾:台湾科技大学,2006.
    [13]孙菁,潘长学.感性工学在产品配色设计中的应用研究[J].包装工程,2007,28(5):91-93.
    [14]Nakanishi S, Takagi T, Nishiyama T. Color planning by fuzzy set theory[C]. IEEE Intemational Conference on Fuzzy Systems. USA:San Diego,1992:5-12.
    [15]Nagamachi M. Kansei engineering as a powerful consumer-oriented technology for product development [J].Applied Ergonomics,2002,33(3):289-294.
    [16]Baek S, Hwang M, Chung H, et al. Kansei factor space classified by information for Kansei image modeling [J].Applied Mathematics and Computation,2008,205(2):874-882.
    [17]Roy R, Goatman M, Khangura K. User-centric design and Kansei Engineering [J]. CIRP Journal of Manufacturing Science and Technology,2009,1(3):172-178.
    [18]Yan H B, Huynh V N, Murai T, et al. Kansei evaluation based on prioritized multi-attribute fuzzy target-oriented decision analysis [J]. Information Sciences,2008,178(21):4080-4093.
    [19]Lai H H, Lin Y C,Yeh C H,et al. User-oriented design for the optimal combination on product design [J]. Int. J. Production Economics,2006,100(2):253-267.
    [20]黄琦,孙守迁.基于意象认知模型的汽车草图设计技术研究[J].浙江大学学报(工学版),2006,40(4):553-559.
    [21]徐江,孙守迁,张克俊.基于遗传算法的产品意象造型优化设计[J].机械工程学报,2007,43(4):53-64.
    [22]邝俊生,江平宇.基于感性工学的产品客户化配置设计[J].计算机辅助设计与图形学学报,2007,19(2):178-183.
    [23]苏建宁,江平宇,李鹤岐等.计算机辅助造型设计支持系统构建方法研究[J].计算机集成制造系统—CIMS,2003,19:61-64.
    [24]Tsai H C, Chou J R. Automatic design support and image evaluation of two-coloured products using colour association and colour harmony scales and genetic algorithm [J]. Computer-Aided Design,2007,39(9):818-828.
    [25]林彦呈.应用软性计算于产品造型与色彩之研究[D].台湾:国立成功大学,2004.
    [26]小林重顺.色彩形象坐标[M].北京:人民美术出版社,2006.
    [27]王庆斌.解析产品色彩调查方法及步骤[J].江南大学学报(人文社会科学版),2006,5(5):115-119.
    [28]张军,赵江洪.意象尺度法与产品设计研究[J].装饰,2002,7:21.
    [29]Hsiao S W. Fuzzy set theory on car-color design [J]. Color Research and Application, 1994,19(3):202-13.
    [30]Hsiao S W. A systematic method for color planning in product design [J]. Color Research and Application,1995,20(3):191-205.
    [31]Ishihara S, Ishihara K, Nagamachi M, et al. An automatic builder for a Kansei expert system using self-organizing neural networks [J]. International Journal of Industrial Ergonomics, 1995,15(1):13-24.
    [32]小林重顺.形象配色艺术[M].北京:人民美术出版社,2006.
    [33]南云治嘉.东方配色[M].北京:中国青年出版社,2007
    [34]Chuang M C, Ou L C. Influence of a holistic color interval on color harmony[J].Color Research and Application,2001,26(1):29-39.
    [35]Tokumaru M, Muranaka N, Imanishi S. Color Design Support System Considering Color Harmony [C].2002 IEEE International Conference on Fuzzy Systems, Honolulu, HI,USA,2002:378-383.
    [36]赵江红,欧静,张军.色彩意象尺度在数控机床ICAID系统中的研究及应用[J].湖南大学学报(自然科学版),2004,31(6):83-86.
    [37]Hard A, Sivik L. A theory of colors in combination-A descriptive model related to the NCS color-order system [J]. Color Research and Application,2001,26(1):4-28.
    [38]马天颖.计算机辅助色彩评价系统[D].西安:西北工业大学,2000.
    [39]张妍.基于语义空间的计算机辅助色彩设计研究[D].西安:两北工业大学,2003.
    [40]Ma M Y, Chen C Y, Wu F G. A design decision-making support model for customized product color combination [J]. Computers in Industry,2007,58(6):504-518.
    [41]Hsiao S W, Tsai H C. Use of Gray System Theory in Product-Color Planning [J].Color Research & Application,2004,29(3):222-231.
    [42]Tsai H C,Hung C Y, Hung F K. Computer aided product color design with artificial intelligence[J]. Computer-Aided Design & Applications,2007,4(1):557-564.
    [43]Tsai H C, Hung C Y, Hung F K. Automatic Product Color Design Using Genetic Searching[C]. Proceedings of the 12th International CAADFutures Conference,2007:513-524.
    [44]Burchett K E. Color harmony [J].Color Research & Application,2002,27(1):28-31.
    [45]郑守益.双色配色意象认知的分析与视觉化[D].台湾:国立台湾科技大学,2002.
    [46]陈昱帆.配色面积对于色彩意象值影响[D].台湾:国立成功大学,2008.
    [47]高淑玲.色彩认知和配色感觉之研究—以改变配色形状和面积对比色彩意象影响为例[D].台湾:国立云林科技大学,2004.
    [48]管伟生,林彦呈.应用类神经网络于手机色彩与造型搭配之研究[J]. Journal of the Chinese Institute of Industrial Engineers,2001,18(6):84-94.
    [49]Tsai H C, Hsiao S W, Hung F K. An image evaluation approach for parameter-based product form and color design[J]. Computer-Aided Design,2006,38(2):157-171.
    [50]张全.产品色彩智能设计理论与研究方法[D].西安:西北工业大学,2007.
    [51]Hsiao S W, Hung F K, Chen C S. Applying a hybrid approach based on fuzzy neural network and genetic algorithm to product form design[J]. International Journal of Industrial Ergonomics,2008,38(2):910-920.
    [52]林颖成.从色彩认知探讨塑胶太阳镜的配色[D].台湾:国立台湾科技大学,2007.
    [52]刘明忠.色彩质感与属性特征对分类辨识与意象差异之研究—以滑鼠为例[D].台湾:国立云林科技大学,2004.
    [54]陈惠文.基因演算法于塑料产品色彩与透明度之感知评价研究[D].台湾:南华大学,2007.
    [55]张玲俐,鲁东明,潘云鹤.计算机辅助色彩协调设计系统[J].计算机工程,1999,25(10):77-80.
    [56]柴春雷,孙守迁,黄琦,等.基于美学标准的产品色彩评价模型的研究[C].第五届全球智能控制与自动化大会,中国杭州,2004:3962-3966.
    [57]宫兴亮.支持自顶向下色彩设计的模型建构与应用[D].西安:西北工业大学,2007.
    [58]龚光红,王行仁,彭晓源等.先进分布仿真技术的发展与应用[J].系统仿真学报,2004,16(2):222-230.
    [59]彭颖红,胡洁.KBE技术及其在产品设计中的应用[M].上海:海交通大学出版社,2007.
    [60]郦洪源.基于UG的零件库建库技术的研究与实现[D].无锡:江南大学,2007.
    [61]熊志勇.基于知识工程的产品创新设计关键技术研究[D].武汉:武汉理工大学,2007.
    [62]谭浩.基于案例的产品造型设计情境知识模型的构建与应用[D].湖南:湖南大学,2006.
    [63]谢友柏.现代设计理论和方法的研究[J].机械工程学报,2004,4:1-9.
    [64]谢友柏.现代设计与知识获取[J].中国机械工程,1996,6:36-41.
    [65]Wallace K.Capturing, Storing and Retrieving Design Knowledge in a Distributed Environment[C]. Proceedings of the 9th International Conference on Computer Supported Cooperative Work in Design, Coventry, USA,2005:10.
    [66]Owen C L. Design Research-Building the Knowledge Base[J]. Design Studies,1998, 19(1):9-20.
    [67]Teixeira J C. Applying Design Knowledge to Create Innovative Business Opportunities [D].US:Illinois Institute of Technology,2001.
    [68]Sakol T, Keiichi S. Object-Mediated User Knowledge Elicitation Method:A Methodology in Understanding User Knowledge[C]. Proceeding of the 5th Asian International Design Research Conference, Korea:Seoul,2001:21-27.
    [69]Sakol T. An approach to user knowledge and product architecture for knowledge lifecycle[D]. US:Illinois Institute of Technology,2002:21-76.
    [70]刘旻,李原,杨海成.产品色彩设计中的知识组织与应用[J].中国机械工程,2002,13(7):565-569.
    [71]苑寅秋.面向机电产品的色彩设计专家系统(MCSES)研究[D].南京:南京航空航天大学,2001.
    [72]王志浩.基于钉枪色彩设计的知识表达与推理研究[D].杭州:浙江工业大学,2008.
    [73]刘肖健,陆长德,李桂琴.色彩配置方案的抽取与设计重用CAD方法研究[J].计算机工程与应用,2004,27:32-33.
    [74]王可,陆长德,余隋怀.面向计算机辅助工业设计的色彩设计系统[J].计算机辅助设计与图形学学报,2004,16(10):1425-1429.
    [75]苏畅.对汽车色彩设计的初步研究[D].吉林:吉林大学,2005.
    [76]苟秉宸.计算机辅助色彩配置理论研究[D].西安:西北工业大学,2000.
    [77]蔡波,陆长德,余隋怀,等.计算机辅助色彩设计系统的构造方法研究[J].西北工业大学学报,2002,18(3):53-56.
    [78]邢文训,谢金星.现代优化计算方法[M].北京:清华大学出版社,1999.
    [79]王凌.智能优化算法及其应用[M].北京:清华大学出版社,2001.
    [80]袁希.微粒群算法与聚类分析在色彩设计中的应用[D].山东:山东师范大学,2008.
    [81]王可,陆长德,乐万德.基于Lab均匀色彩空间的色彩调和系统[J].西北工业大学学报,2004,22(6):695-699.
    [82]王聪,余隋怀,苟秉宸,等.CACD系统中色调调和配色方法研究[C].2005年工业设计国际会议论文集.中国:武汉,2005:455-499.
    [83]欧静,赵江洪.基于色彩调和理论的数控机床色彩评价研究[J].包装工程,2007,28(1):158-160.
    [84]姚小清.基于色立体的产品色彩设计技术研究[D].保定:华北电力大学,2006.
    [85]王可.计算机辅助色彩设计理论和方法研究[D].西安:西北工业大学,2006.
    [86]石源.计算机辅助产品色彩设计工具集的研究[D].西安:西北工业大学,2004.
    [87]张宪荣,张萱.设计色彩学[M].北京:化学工业出版社,2003.
    [88]李玉凤,张宪荣.现代色彩调和理论的工程化评价方法[J].包装工程,2002,23(3):152-156.
    [89]李玉凤,黄义萍.色彩设计的定量化理性化方法研究[J].包装工程,2004,25(6):92-94.
    [90]Moon P, Spencer D E. Geometric formulation of classical color harmony [J]. Journal of the optical society of america,1944,34(1):46-60.
    [91]Moon P,Spencer D E. Area in Color Harmony [J], Journal of the optical society of america,1944,34(2):93-103.
    [92]Moon P, Spencer D E. Aesthetic Measure Applied to Color Harmony [J]. Journal of the optical society of america,1944,34(4):234-242.
    [93]马沁怡.客户需求导向的产品设计方法研究[D].大连:大连理工大学,2004.
    [94]孙菁,王少梅,朱明键.基于灰色理论的产品配色意象值评价算法研究[J].武汉理工大学学报(交通科学与工程版),2007,31(3):453-456.
    [95]邓聚龙.灰色系统基本方法[M].武汉:华中科技大学出版社,2005.
    [96]罗佑新,张龙庭,李敏.灰色系统理论及其在机械工程中的应用[M].长沙:国防科技大学出版社,2001.
    [97]孙菁.基于意象的产品造型设计方法研究[D].武汉:武汉理工大学,2007.
    [98]郑国裕,林磐耸.色彩计划[M].台北:艺风堂出版社,2002.
    [99]李亮之.色彩设计[M].北京:高等教育出版社,2006.
    [100]朱介英.色彩学[M].北京:中国青年出版社,2006.
    [101]Zhang X, Huang H Z, Yu L F. Fuzzy Preference based Interactive Fuzzy Physical Programming and its Application in Multi-objective Optimization [J]. Journal of Mechanical Science and Technology,2006,20(6):731-737.
    [102]Suganthan P N. Particle Swarm Optimizer with Neighborhood Operator [C]. Proceedings of the IEEE Congress off Evolutionary Computation. USA:Washington, DC,1999:1958-1961.
    [103]Shi Y, Eberhart R. Fuzzy Adaptive Particle Swarm Optimization [C]. Proceedings of the IEEE Congress on Evolutionary Computation, Korea:Seoul,2001:79-85.
    [104]Kennedy J, Eberchart R C. Particle Swarm Optimization[C]. Proceedings of the IEEE International Conference on Neural Networks. Australia:Perth,1995,1942-1948.
    [105]He S,Wu Q H, Wen J Y, et al.A Particle Swarm Optimizer with Passive Congregation[J]. BioSystems,2004,78(1-3):135-147.
    [106]王俊伟.粒子群优化算法的改进及应用[D].沈阳:东北大学,2006.
    [107]Thorndike E L. Animal Intelligence:Empirical Studies[M]. New York:MacMillan,1911.
    [108]Kennedy J. The particle swarm:social adaptation of knowledge [C]. Proceedings IEEE International conference on Evolutionary Computation,India:Mapolis,1997,303-308.
    [109]Bandura A. Social Foundation of Thought and Action:A Social Cognitive Theory [M].New Jersey:Prentice Hall,1986.
    [110]Ou L C, Luo M R, Woodcock A, et al. A Study of Colour Emotion and Colour Preference. Part I:Colour Emotions for Single Colours [J]. Color research and application,2003, 29(3):232-240.
    [111]Ou L C, Luo M R, Woodcock A, et al.A Study of Colour Emotion and Colour Preference. Part II:Colour Emotions for Two-Colour Combinations [J]. Color research and application, 2003,29(4):292-298.
    [112]Ou L C, Luo M R, Woodcock A, et al. A Study of Colour Emotion and Colour Preference. Part III:Colour Preference Modeling [J].Color research and application,2004,29 (5):381-389.
    [113]高国斌.高龄化色彩意象与喜好度之调查研究[D].台湾:东海大学,2001.
    [114]沈旻玮.多重感性语意间之复合型探讨[D].台湾:国立云林科技大学,2003.
    [115]S. H. Hsu, M.C. Chuang, C. C. Chang. A semantic differential study of designers'and users'product form perception [J], International Journal of Industrial Ergonomics,2000, 25(4):375-391.
    [116]K. A. Hsiao, L. L. Chen. Fundamental dimensions of affective responses to product shapes [J], International Journal of Industrial Ergonomics,2006,36(6):553-564.
    [117]E. Alcantara, M. A. Artacho, J. C. Gonzalez et al. Application of product semantics to footwear design. Partl-Identification of footwear semantic space applying differential semantics [J]. International Journal of Industrial Ergonomics,2005,35(8):713-725.
    [118]M. C. Chuang, C. C. Chang, S. H. Hsu. Perceptual factors underlying user preferences toward product form of mobile phones [J]. International Journal of Industrial Ergonomics, 2001,27(4):247-258.
    [119]M. D. Shieh, C.C. Yang. Classification model for product form design using fuzzy support vector machines [J]. Computers & Industrial Engineering,2008,55(1):150-164.
    [120]C. C. Yang, M. D. Shieh. A support vector regression based prediction model of affect ive responses for product form design [J]. Computers & Industrial Engineering,2010,59 (4), 682-689.
    [121]C. Goodall. Procrustes methods in the statistical analysis of shape [J]. Journal of Royal Statistic Society,1991,53(2):285"339.
    [122]Chih-Chieh Yang. A classification-based Kansei engineering system for modeling consumers'affective responses and analyzing product form features [J]. Expert Systems with Applications,2011,38(9):11382-11393.
    [123]关志华,寇纪淞,李敏强.基于模糊偏好的多目标进化优化算法[J].天津大学学报,2002,35(3):275-280.
    [124]许焕卫,黄洪钟,张旭.基于模糊折中规划的稳健多目标优化设计[J].大连理工大学学报,2007,47(4):368-371.
    [125]J. C. Nunnally, Psychometric Theory.1967, USA:McGraw-Hill.
    [126]J.0. Kim & C. W. Mueller, Factor Analysis:Statistical Methods and Practical Issues, d.. U. P. S. o. Q. A. i. S. Sciences.1978, Newbury Park:Sage Publication.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700