基于犹豫倾向聚类的物流中心选址方法
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摘要
针对现有直觉模糊相似度量存在的不足,文中提出了考虑带倾向性相似度的直觉模糊相似度量公式,通过构建相似矩阵和等价相似矩阵以及截矩阵,给出新颖的直觉模糊集聚类方法,对物流中心选址问题的应用分析,验证了聚类方法的合理性与有效性。
Aiming at the shortcomings of existing intuitionistic fuzzy similarity measure, this paper proposes an intuitionistic fuzzy similarity measure formula with tendency similarity. By constructing similar matrix, equivalent similarity matrix and cutting matrix, a novel intuitionistic fuzzy set clustering method is presented. The application analysis of the location selection of logistics center verifies the rationality and effectiveness of the clustering method.
Aiming at the shortcomings of existing intuitionistic fuzzy similarity measure, this paper proposes an intuitionistic fuzzy similarity measure formula with tendency similarity. By constructing similar matrix, equivalent similarity matrix and cutting matrix, a novel intuitionistic fuzzy set clustering method is presented. The application analysis of the location selection of logistics center verifies the rationality and effectiveness of the clustering method.
引文
[1] Zadeh L A. Fuzzy sets[J]. Information & Control, 1965, 8(3): 338-353.
[2] Atanassov K T. Intuitionistic fuzzy sets[J]. Control Theory & Applications, 1986, 20(1): 87-96.
[3] Ye J. Multicriteria fuzzy decision-making method using entropy weights-based correlation coefficients of interval-valued intuitionistic fuzzy sets[J]. Applied Mathematical Modelling, 2010, 34(12): 3864-3870.
[4] Zhang Q. Study on the software quality evaluation based on artificial intelligence with intuitionistic fuzzy information[J]. International Journal of Digital Content Technology & Its Applications, 2012, 6(22): 371-376.
[5] Le H S, Thong N T. Intuitionistic fuzzy recommender systems: an effective tool for medical diagnosis[J]. Knowledge-Based Systems, 2015, 74(1): 133-150.
[6] Liao H, Xu Z, Zeng X J, et al. An enhanced consensus reaching process in group decision making with intuitionistic fuzzy preference relations[J]. Information Sciences, 2016, 329(C): 274-286.
[7] Meng F, Chen X. Entropy and similarity measure of atanassov’s intuitionistic fuzzy sets and their application to pattern recognition based on fuzzy measures[J]. Pattern Analysis & Applications, 2016, 19(1): 11-20.
[8] Guha D, Chakraborty D. A new similarity measure of intuitionistic fuzzy sets and its application to estimate the priority weights from intuitionistic preference relations[J]. Notes on Instuitionistic Fuzzy Sets, 2012, 18: 37- 47.
[9] Chen S M. Measures of similarity between vague sets[J]. Fuzzy Sets & Systems, 1995, 74(2): 217-223.
[10] Hong D H, Kim C. A note on similarity measures between vague sets and between elements[J]. Information Sciences, 1999, 115(1): 83-96.
[11] 李凡,徐章艳.Vague集之间的相似度量[J].软件学报,2001,12(6):922-927.
[12] Li Y, Olson D L, Qin Z. Similarity measures between intuitionistic fuzzy(vague)sets: a comparative analysis[J]. Pattern Recognition Letters, 2007, 28(2): 278-285.
[13] Mitchell H B. On the Dengfeng-chuntian similarity measure and its application to pattern recognition[J]. Pattern Recognition Letters, 2003, 24(16): 3101-3104.
[14] Li D, Cheng C. New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions[J]. Pattern Recognition Letters, 2002, 23(1): 221-225.
[15] Gao F, Zhao Z X, Wen G J, et al. Modeling of the uncertainty of image features and their similarity computing based on vague sets[J]. Acta Electronica Sinica, 2011, 39(11): 2622-2626.
[16] Hwang C M, Yang M S, Hung W L, et al. A similarity measure of intuitionistic fuzzy sets based on the sugeno integral with its application to pattern recognition[J]. Information Sciences, 2012, 189(6): 93-109.
[17] Iancu I. Intuitionistic fuzzy similarity measures based on Frank t-norms family[J]. Pattern Recognition Letters, 2014, 42: 128-136.
[18] Chen S M, Tan J M. Handling multicriteria fuzzy decision-making problems based on vague set theory[J]. Fuzzy sets and systems, 1994, 67(2): 163-172.
[19] 雷英杰.直觉模糊集理论及应用.上册[M].科学出版社,2014.
[20] Bustince H, Burillo P. Vague sets are intuitionistic fuzzy sets[J]. Fuzzy Sets & Systems, 1996, 79(3): 403- 405.
[21] Xu Z, Chen J, Wu J. Clustering algorithm for intuitionistic fuzzy sets[J]. Information Sciences, 2008, 178(19): 3775-3790.
[2] Atanassov K T. Intuitionistic fuzzy sets[J]. Control Theory & Applications, 1986, 20(1): 87-96.
[3] Ye J. Multicriteria fuzzy decision-making method using entropy weights-based correlation coefficients of interval-valued intuitionistic fuzzy sets[J]. Applied Mathematical Modelling, 2010, 34(12): 3864-3870.
[4] Zhang Q. Study on the software quality evaluation based on artificial intelligence with intuitionistic fuzzy information[J]. International Journal of Digital Content Technology & Its Applications, 2012, 6(22): 371-376.
[5] Le H S, Thong N T. Intuitionistic fuzzy recommender systems: an effective tool for medical diagnosis[J]. Knowledge-Based Systems, 2015, 74(1): 133-150.
[6] Liao H, Xu Z, Zeng X J, et al. An enhanced consensus reaching process in group decision making with intuitionistic fuzzy preference relations[J]. Information Sciences, 2016, 329(C): 274-286.
[7] Meng F, Chen X. Entropy and similarity measure of atanassov’s intuitionistic fuzzy sets and their application to pattern recognition based on fuzzy measures[J]. Pattern Analysis & Applications, 2016, 19(1): 11-20.
[8] Guha D, Chakraborty D. A new similarity measure of intuitionistic fuzzy sets and its application to estimate the priority weights from intuitionistic preference relations[J]. Notes on Instuitionistic Fuzzy Sets, 2012, 18: 37- 47.
[9] Chen S M. Measures of similarity between vague sets[J]. Fuzzy Sets & Systems, 1995, 74(2): 217-223.
[10] Hong D H, Kim C. A note on similarity measures between vague sets and between elements[J]. Information Sciences, 1999, 115(1): 83-96.
[11] 李凡,徐章艳.Vague集之间的相似度量[J].软件学报,2001,12(6):922-927.
[12] Li Y, Olson D L, Qin Z. Similarity measures between intuitionistic fuzzy(vague)sets: a comparative analysis[J]. Pattern Recognition Letters, 2007, 28(2): 278-285.
[13] Mitchell H B. On the Dengfeng-chuntian similarity measure and its application to pattern recognition[J]. Pattern Recognition Letters, 2003, 24(16): 3101-3104.
[14] Li D, Cheng C. New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions[J]. Pattern Recognition Letters, 2002, 23(1): 221-225.
[15] Gao F, Zhao Z X, Wen G J, et al. Modeling of the uncertainty of image features and their similarity computing based on vague sets[J]. Acta Electronica Sinica, 2011, 39(11): 2622-2626.
[16] Hwang C M, Yang M S, Hung W L, et al. A similarity measure of intuitionistic fuzzy sets based on the sugeno integral with its application to pattern recognition[J]. Information Sciences, 2012, 189(6): 93-109.
[17] Iancu I. Intuitionistic fuzzy similarity measures based on Frank t-norms family[J]. Pattern Recognition Letters, 2014, 42: 128-136.
[18] Chen S M, Tan J M. Handling multicriteria fuzzy decision-making problems based on vague set theory[J]. Fuzzy sets and systems, 1994, 67(2): 163-172.
[19] 雷英杰.直觉模糊集理论及应用.上册[M].科学出版社,2014.
[20] Bustince H, Burillo P. Vague sets are intuitionistic fuzzy sets[J]. Fuzzy Sets & Systems, 1996, 79(3): 403- 405.
[21] Xu Z, Chen J, Wu J. Clustering algorithm for intuitionistic fuzzy sets[J]. Information Sciences, 2008, 178(19): 3775-3790.