[1] A P Dempster.Upper and lower probabilities induced by a multivalued mapping[J].The Annals of Mathematical Statistics,1967,38(2):325-339. [2] 徐从富,耿卫东,潘云鹤.面向数据融合的DS方法综述[J].电子学报,2001,29 (3):393-396. XU Cong-fu,GENG Wei-dong,PAN Yun-he.Review of Dempster-Shafer method for data fusion[J].Acta Electronica Sinica,2001,29(3):393-396.(in Chinese) [3] P Smets,R Kennes.The transferable belief model[J].Artificial Intelligence,1994,66:191-243. [4] 孙怀江,杨静宇.一种相关证据合成方法[J].计算机学报,1999,22(3):1004-1007. [5] 刘明,袁保宗,唐晓芳.证据理论k-NN规则中确定相似度参数的新方法[J].电子学报,2005,33(4):766-768. LIU Ming, YUAN Bao-zong,TANG Xiao-fang.A new approach to determine the similarity parameters in evidence-theoretic k-NN rule[J].Acta Electronica Sinica,2005,33(4):766-768.(in Chinese) [6] 何兵.基于分类及不确定墒的DS证据合成及判决方法[J].北京航空航天大学学报,2003,29(10):927-930. [7] 邓勇,施文康.一种改进的证据推理组合规则[J].上海交通大学学报,2003,37(8):1275-1278. [8] 高社生,倪龙强,杨凯.一种新的基于局部冲突分配的证据合成规则[J].西北工业大学学报,2009,27(1):43-46. [9] 韩德强,韩崇昭,邓勇,等.基于证据方差的加权证据组合[J].电子学报,2011,39(3A):153-157. HAN De-qiang,HAN Chong-zhao,DENG Yong,et al.Weighted combination of conflicting evidence based on evidence variance[J].Acta Electronica Sinica,2011,39(3A):153-157.(in Chinese) [10] 肖明珠,陈光.一种改进的证据合成公式[J].电子学报,2005,33(9):1714-1716. XIAO Ming-zhu,CHEN Guang-ju.A modified combination rule of evidence theory. Acta Electronica Sinica,2005,33(9):1714-1716.(in Chinese) [11] 郎风华,谷利泽,杨义先,等.一种基于均衡交补分担准则的证据组合新方法[J].电子学报,2009,37(1):95-100. LANG Feng-hua,GU Li-ze,YANG Yi-xian,et al.A novel evidence combination method based on proportional conjunctive and complementary pooling criterion[J].Acta Electronica Sinica,2009,37(1):95-100.(in Chinese) [12] 郭华伟,施文康,邓勇,等.一种通用的不确定性推理和决策模型[J].传感技术学报,2006,(4):1176-1180. [13] Ronald R Yager.On the Dempster-Shafer framework and new combination rules[J].Information Sciences,1987,41(2):93-138. [14] C K Murphy.Combining belief functions when evidence conflicts[J].Decision Support Systems,2000,29(1):1-9. [15] 孙全,叶秀清,顾伟康.一种新的基于证据理论的合成公式[J].电子学报,2000,28(8):117-119. SUN Quan,YE Xiu-qing,GU Wei-kang.A new combination rules of evidence theory. Acta Electronica Sinica,2000,28(8):117-119.(in Chinese) [16] J W Guan,D A Bell.Approximate reasoning and evidence theory[J].Information Science,1997,96:207-235. [17] R Kruse.Uncertainty and Vagueness in Knowledge Based Systems:Numerical Methods. New York:Springer-Verlag,1991. [18] E Lefevre,P Vannoorenberglle,O Colot.About the use of Dempster-Shafer theory for color image segmentation. First International Conference on Color in Graphics and Image Processing. Saint-Etienne,France:CEPADUES,2000.164-169. [19] A L Jousselme,éloi Bossé,D Grenier.A new distance between two bodies of evidence [J].Information Fusion,2001,2(2):91-101. [20] 潘泉,张山鹰,程咏梅,等.证据推理的鲁棒性研究[J].自动化学报,2001,27(6):799-805. [21] W Liu.Analyzing the degree of conflict among belief function[J].Artificial Intelligence,2006,170:909-924. [22] 许培达,韩德强,邓勇.一种基本概率赋值转换为概率的最优化方法[J].电子学报, 2011,39(3A):121-125. XU Pei-da,HAN De-qiang,DENG Yong.An optimal transformation of basic probability assignment to probability[J].Acta Electronica Sinica,2011,39(3A):121-125.(in Chinese) [23] Zadeh L.On the Validity of Dempster’s Rule of Combination of Evidence. Berkely:University of California,1979. [24] F Smarandache,J Dezert.Information fusion based on new proportional conflict redistribution rules. Proc of the 2005 8th Int Conf on Information Fusion. Philadelphia:IEEE,2005.907-914. |