[1]孙怀江,杨静宇.λ-模糊测度辨识方法研究[J].南京理工大学学报(自然科学版),2001,(01):44-47.
 SunHuaijiang YangJingyu.A Study on Identification Methods of λ-Fuzzy Measures[J].Journal of Nanjing University of Science and Technology,2001,(01):44-47.
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λ-模糊测度辨识方法研究()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
期数:
2001年01期
页码:
44-47
栏目:
出版日期:
2001-02-28

文章信息/Info

Title:
A Study on Identification Methods of λ-Fuzzy Measures
作者:
孙怀江杨静宇
南京理工大学计算机科学与技术系!南京210094
Author(s):
SunHuaijiang YangJingyu
Department of Computer Science and Technology,NUST,Nanjing 210094
关键词:
人工智能 模式识别 测度( 数学)
Keywords:
artificial intelligence pattern recognit ion meas
分类号:
TP18
摘要:
研究了当专家给出的模糊测度具有不确定性时λ-模糊测度的辨识问题 ,不确定数据分别用区间和模糊数来表达 ,针对不同情况提出了 4种误差函数 ,误差函数的最小值对应于最优的辨识结果 ,而且当不存在不确定性时 ,所得结果与目前已有方法相同。数值实验结果表明 ,该文提出的辨识方法是有效的
Abstract:
Fuzzy measures g iven by human ex pert s usually contain uncertaint ies, and do not sat isfy required mathemat ical properties. The problem of ident ifying lambda-fuzzy measures is studied w hen the uncertaint ies are expressed by intervals and fuzzy numbers. Four error funct ions are proposed. The minima of error functions correspond to opt imal ident ified results. When there is not any uncertainty, obtained results are equal to those from exist ing methods. Numerical experimental result s indicate that the proposed ident if icat ion algorithms are ef ficient .

参考文献/References:

1 Tahani H, Keller J M. Informatio n fusion in computer vision using the fuzzy integr al. IEEE Trans SMC, 1990, 20( 3) : 733~ 741
2 Leszczynski K, Penczek P, Grochulski W. Sug eno. s fuzzy measure and fuzzy cluster ing . Fuzzy Sets and Systems, 1985, 15( 2) : 147~ 158
3 Wier zchon S T. An alg orithm for identificat ion of fuzzy measure. Fuzzy Sets and Systems, 1983,9( 1) : 69~ 78
4 Lee K M, Leekw ang H. Ident ification of K-fuzzy measure by g enetic alg orithms. Fuzzy Sets and Systems, 1995, 75( 3) : 301~ 309

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备注/Memo

备注/Memo:
国防科技预研行业基金项目
孙怀江 男 33 岁 副教授
更新日期/Last Update: 2013-03-25