基于改進(jìn)沖突度量的多證據(jù)直接融合算法
doi: 10.11999/JEIT180578
-
1.
魯東大學(xué)信息與電氣工程學(xué)院 ??煙臺 ??264025
-
2.
華東師范大學(xué)外國語學(xué)院 ??上海 ??200241
A Direct Fusion Algorithm for Multiple Pieces of Evidence Based on Improved Conflict Measure
-
1.
School of Information and Electrical Engineering, Ludong University, Yantai 264039, China
-
2.
School of Foreign Languages, East China Normal University, Shanghai 200241, China
-
摘要:
針對Jousselme證據(jù)距離函數(shù)不能較好描述證據(jù)局部沖突和不能對高沖突證據(jù)進(jìn)行準(zhǔn)確沖突度量的不足，該文首先提出改進(jìn)的Jousselme證據(jù)距離函數(shù)，該函數(shù)基于能夠較好描述證據(jù)之間局部沖突情況的非重合度對Jousselme證據(jù)距離函數(shù)進(jìn)行改進(jìn)，使其沖突度量結(jié)果隨非重合度取值及其取值范圍的變化按適當(dāng)比例進(jìn)行變化；其次，基于沖突系數(shù)和新改進(jìn)Jousselme證據(jù)距離函數(shù)共同構(gòu)建改進(jìn)的融合沖突度量函數(shù)。在此基礎(chǔ)上，對焦元權(quán)系數(shù)計(jì)算式進(jìn)行改進(jìn)，并依此對局部多維沖突信息進(jìn)行按比例分配。理論及應(yīng)用分析結(jié)果表明，新算法是一種適用性廣泛且抗干擾性能好的證據(jù)融合算法。
-
關(guān)鍵詞:
- Dempster證據(jù)組合規(guī)則 /
- 沖突度量 /
- 證據(jù)距離 /
- 非重合度
Abstract:In the light of the disadvantages that Jousselme’s evidential distance function can not describe the local conflicting information of evidence well and can not measure the conflict of high conflicting evidence accurately, an improved Jousselme’s evidential distance function is proposed. In the new function, Jousselme’s evidence distance function is improved by using the non-coincidence degree, which can better describe the local conflict of evidence, so that the conflict measure result of evidence varies proportionally with the value of the non-coincidence degree and the scope of its change. Secondly, an improved fusion conflict measure function is constructed based on the conflict coefficient and the new improved Jousselme’s evidential distance function. On this basis, the weight coefficient formula of focal element is improved, and the local multi-dimensional conflicting information is assigned proportionately. Theoretical and application analysis results show that the new algorithm is a kind of evidence fusion algorithm with wide applicability and good anti-jamming performance.
-
表 1 不同參數(shù)對情況1中證據(jù)的沖突度量結(jié)果
沖突度量參數(shù) ${m_1}$與${m_1}$ ${m_2}$與${m_2}$ ${m_1}$與${m_2}$ ${d_J}$ 0 0 0.4500 $k$ 0.4600 0.5050 0.6850 ${n_c}$ 0 0 0.4500 ${d_{{\rm{PJ}}}}$ 0 0 0.6255 ${d_{{\rm{NIJ}}}}(\gamma {\rm{ = 4)}}$ 0 0 0.7618 ${d^f}(\gamma {\rm{ = 4)}}$ 0.2652 0.2964 0.7241 
下載: 導(dǎo)出CSV
表 2 不同參數(shù)對情況2中證據(jù)的沖突度量結(jié)果
沖突度量參數(shù) ${m_1}$與${m_1}$ ${m_2}$與${m_2}$ ${m_1}$與${m_2}$ ${d_J}$ 0 0 0.8352 $k$ 0 0.4050 0.9000 ${n_c}$ 0 0 0.9000 ${d_{{\rm{PJ}}}}$ 0 0 0.9352 ${d_{{\rm{NIJ}}}}(\gamma {\rm{ = 8)}}$ 0 0 0.9886 ${d^f}(\gamma {\rm{ = 8)}}$ 0 0.2287 0.9662
下載: 導(dǎo)出CSV
-
SHAFER G. A mathematical theory of evidence turns 40[J]. International Journal of Approximate Reasoning, 2016, 79: 7–25. doi: 10.1016/j.ijar.2016.07.009 HAN Deqiang, DEZERT J, and YANG Yi. Belief interval-based distance measures in the theory of belief functions[J]. IEEE Transactions on Systems Man & Cybernetics Systems, 2016, 99: 1–18. doi: 10.1109/TSMC.2016.2628879 韓德強(qiáng), 楊藝, 韓崇昭. DS證據(jù)理論研究進(jìn)展及相關(guān)問題探討[J]. 控制與決策, 2014, 29(1): 1–11. doi: 10.13195/j.kzyjc.2013.0517HAN Deqiang, YANG Yi, and HAN Chongzhao. Advances in DS evidence theory and related discussions[J]. Control and Decision, 2014, 29(1): 1–11. doi: 10.13195/j.kzyjc.2013.0517 DESTERCKE S and BURGER T. Toward an axiomatic definition of conflict between belief functions[J]. IEEE Transactions on Cybernetics, 2013, 43(2): 585–596. doi: 10.1109/TSMCB.2012.2212703 ZADEH L A. A simple view of the Dempster-Shafer theory of evidence and its implication for the rule of combination[J]. AI magazine, 1986, 7(2): 85–90. doi: 10.1142/9789814261302-0033 SONG Yafei, WANG Xiaodan, LEI Lei, et al. Credibility decay model in temporal evidence combination[J]. Information Processing Letters, 2015, 115(2): 248–252. doi: 10.3969/j.issn.1001-506X.2015.07.04 BI Wenhao, ZHANG An, and YUAN Yuan. Combination method of conflict evidences based on evidence similarity[J]. Journal of Systems Engineering and Electronics, 2017, 28(3): 503–513. doi: 10.21629/JSEE.2017.03.10 QIAN Jin, GUO Xingfeng, and DENG Yong. A novel method for combining conflicting evidences based on information entropy[J]. Applied Intelligence, 2017, 46(4): 1–13. doi: 10.1007/s10489-016-0875-y 包甜甜, 謝新連, 魏照坤. 新的證據(jù)沖突度量算法[J]. 控制理論與應(yīng)用, 2017, 34(1): 41–48. doi: 10.7641/CTA.2017.60275BAO Tiantian, XIE Xinlian, and WEI Zhaokun. Novel approach for measuring the conflict between evidence[J]. Control Theory &Applications, 2017, 34(1): 41–48. doi: 10.7641/CTA.2017.60275 鄧勇, 施文康, 朱振福. 一種有效處理沖突證據(jù)的組合方法[J]. 紅外與毫米波學(xué)報(bào), 2004, 23(1): 27–32. doi: 10.3321/j.issn:1001-9014.2004.01.006DENG Yong, SHI Wenkang, and ZHU Zhenfu. Efficient combination approach of conflict evidence[J]. Journal of Infrared and Millimeter Wave, 2004, 23(1): 27–32. doi: 10.3321/j.issn:1001-9014.2004.01.006 宋亞飛, 王曉丹, 雷蕾, 等. 基于信任度和虛假度的證據(jù)組合方法[J]. 通信學(xué)報(bào), 2015, 36(5): 98–103. doi: 10.11959/j.issn.1000-436x.2015104SONG Yafei, WANG Xiaodan, LEI Lei, et al. Evidence combination based on the degree of credibility and falsity[J]. Journal on Communications, 2015, 36(5): 98–103. doi: 10.11959/j.issn.1000-436x.2015104 LIU Zhigang, HAN Zhiwei, ZHANG Yang, et al. Multiwavalet packet entropy and its application in transmission line fault recognition and classification[J]. IEEE Transactions on Neural Networks and Learning Systems, 2014, 25(11): 2043–2052. doi: 10.1109/TNNLS.2014.2303086 DENG Yong. Generalized evidence theory[J]. Applied Intelligence, 2015, 43(3): 530–543. doi: 10.1007/s10489-015-0661-2 郭強(qiáng), 何友, 李新德. 一種快速DSmT-DS近似推理融合方法[J]. 電子與信息學(xué)報(bào), 2015, 37(9): 2040–2046. doi: 10.11999/JEIT150086GUO Qiang, HE You, and LI Xinde. Fast DSmT-DS approximate reasoning method[J]. Journal of Electronics &Information Technology, 2015, 37(9): 2040–2046. doi: 10.11999/JEIT150086 周莉, 郭偉震, 曹珊珊. 改進(jìn)的局部沖突信息再分配算法[J]. 光電子激光, 2018, 29(4): 396–404. doi: 10.16136/j.joel.2018.04.0205ZHOU Li, GUO Weizhen, and CAO Shanshan. An improved local conflict information redistribution algorithm[J]. Journal of Optoelectronics Laser, 2018, 29(4): 396–404. doi: 10.16136/j.joel.2018.04.0205 曹潔, 郭雷雷. 一種基于局部沖突分配的證據(jù)組合規(guī)則[J]. 計(jì)算機(jī)應(yīng)用研究, 2013, 30(7): 2033–2035. doi: 10.3969/j.issn.1001-3695.2013.07.029CAO Jie and GUO Leilei. Evidence combination rule based on local conflict distribution strategy[J]. Application Research of Computers, 2013, 30(7): 2033–2035. doi: 10.3969/j.issn.1001-3695.2013.07.029 彭穎, 胡增輝, 沈懷榮. 一種修正證據(jù)距離[J]. 電子與信息學(xué)報(bào), 2013, 35(7): 1624–1629. doi: 10.3724/SP.J.1146.2012.01680PENG Ying, HU Zenghui, and SHEN Huairong. A modified distance of evidence[J]. Journal of Electronics &Information Technology, 2013, 35(7): 1624–1629. doi: 10.3724/SP.J.1146.2012.01680 毛藝帆, 張多林, 王路. 基于重合度的證據(jù)沖突度量方法[J]. 控制與決策, 2017, 32(2): 293–298. doi: 10.13195/j.kzyjc.2016.1394MAO Yifan, ZHANG Duolin, and WANG Lu. Measurement of evidence conflict based on overlapping degree[J]. Control and Decision, 2017, 32(2): 293–298. doi: 10.13195/j.kzyjc.2016.1394 湯潮, 蔣雯, 陳運(yùn)東, 等. 新不確定度量下的沖突證據(jù)融[J]. 系統(tǒng)工程理論與實(shí)踐, 2015, 35(9): 2394–2400. doi: 10.12011/1000-6788(2015)9-2394TANG Chao, JIANG Wen, CHEN Yundong, et al. Conflicting evidence combination based on a new measure method of uncertainty[J]. Systems Engineering -Theory &Practice, 2015, 35(9): 2394–2400. doi: 10.12011/1000-6788(2015)9-2394 BURGER T. Geometric views on conflicting mass functions: From distances to angles[J]. International Journal of Approximate Reasoning, 2016, 70: 36–50. doi: 10.1016/j.ijar.2015.12.006 -
計(jì)量
- 文章訪問數(shù): 1739
- HTML全文瀏覽量: 446
- PDF下載量: 62
- 被引次數(shù): 0
下載:
