正在加载图片...
·756 智能系统学报 第11卷 bination granulation in incomplete information system[] tern recognition and artificial intelligence,2012,25(3): Lecture notes in computer science,2006,4062:184-190. 361-366. [69]WANG Junhong,LIANG Jiye,QIAN Yuhua,et al.Uncer- [81 SHE Yanhong,LI Jinhai,YANG Hailong.A local ap- tainty measure of rough sets based on a knowledge granula- proach to rule induction in multi-scale decision tables[J]. tion for incomplete information systems[J].International Knowledge-based systems,2015,89:398-410. journal of uncertainty,fuzziness and knowledge-based sys- [82]邓大勇,徐小玉,黄厚宽.基于并行约简的概念漂移探 tems,2008,16(2):233-244. 测[J].计算机研究与发展,2015,52(5):1071-1079. [70]梁吉业,钱宇华.信息系统中的信息粒与嫡理论[」] DENG Dayong,XU Xiaoyu,HUANG Houkuan.Concept 中国科学E辑:信息科学,2008,38(12):2048-2065. drifting detection for categorical evolving data based on par- LIANG Jiye,QIAN Yuhua.Information granules and entro- allel reducts[J].Joumal of computer research and devel- py theory in information systems[].Science in China se. opment,.2015,52(5):1071-1079. ries F:information sciences,2008,51(10):1427-1444. [83]徐计,王国胤,于洪.基于粒计算的大数据处理[J刀.计 [71]BAYES T.An essay towards solving a problem in the doc- 算机学报,2015,38(8):1497-1517. trine of chances[J].Philosophical transactions of the royal XU Ji,WANG Guoyin,YU Hong.Review of big data pro- s0 ciety,53(1763):370-418. cessing based on granular computing[J].Chinese journal [72]YU Jianhang,ZHANG Xiaoyan,ZHAO Zhenhua et al. of computers,2015,38(8):1497-1517. Uncertainty measures in multigranulation with different [84]RUAN Junhu,WANG Xuping,SHI Yan.Developing fast grades rough set based on dominance relation[J].Joural predictors for large-scale time series using fuzzy granular of intelligent fuzzy systems,2016,31:1133-1144. support vector machines [J].Applied soft computing, [73 LIN Guoping,LIANG Jiye,QIAN Yuhua.Uncertainty 2013,13(6):3981-4000. measures for multigranulation approximation space[J.In- [85]HE Jieyue,ZHONG Wei,HARRISON R,et al.Clustering ternational journal of uncertainty fuzziness and knowledge- support vector machines and its application to local protein based systems,.2015,23(3)443-457. tertiary structure prediction[C]//Proceedings of the 6th [74]ZHANG Qinghua,ZHANG Qiang,WANG Guoyin.The Interational Conference on Computational Science.Read- uncertainty of probabilistic rough sets in multi-granulation ing,UK:Springer-Verlag,2006:710-717. spaces[].International journal of approximate reasoning, [86]欧阳继红,刘燕辉,李熙铭,等.基于LDA的多粒度主 2016,77:38-54 题情感混合模型[J].电子学报,2015,43(9):1875- [75]苗夺谦.Rough Set理论及其在机器学习中的应用研究 1880 [D].1997,北京,中国科学院自动化研究所 OUYANG Jihong,LIU Yanhui,LI Ximing,et al.Multi- MIAO Duoqian.Rough set theory and its application in ma- grain sentiment/topic model based on LDA[J].Acta elec- chine learning[D].1997,Beijing,Institute of Automa- tronica sinica,2015,43(9):1875-1880. tion,Chinese Academy of Sciences. [87]WANG Xuekuan,ZHAO Cairong,MIAO Duoqian,et al. [76]MA Zhouming,MI Jusheng.A comparative study of Fusion of multiple channel features for person re-identifica- MGRSs and their uncertainty measures[J].Fundamenta tion[J].Neurocomputing,2016,213:125-136. informaticae,2015,142:161-181. [88]XU Weihua,YU Jianhang.A novel approach to information [77]HUANG Bing,GUO Chunxiang,LI Huaxiong,et al.Hier- fusion in multi-source datasets:a granular computing view- arhical structures and uncertainty measures for intuitionistic point[J].Information sciences,2017,378:410-423. fuzzy approximate space[].Information Sciences,2016, [89]LIN Guoping,LIANG Jiye,QIAN Yuhua.et al.A fuzzy 336:92-114. multigranulation decision-theoretic approach to multisource [78]LIANG Jiye,WANG Feng,DANG Chuangyin,et al.An fuzzy information systems J].Knowledge-based systems, efficient rough feature selection algorithm with a multi- 2016.91:102-113. granulation view[J].International journal of approximate [90]http://cncc.ccf.org.cn/struct/7. reasoning,.2012,53(6):912-926. [91]LI Jinhai,HUANG Chenchen,QI Jianjun et al.Three-way [79]LIN Yaojin,LI Jinjin,LI Peirong,et al.Feature selection cognitive concept learning via multi-granularity[J].Infor- via neighborhood multi-granulation fusion[J].Knowledge- mation Sciences.2017,378 244-263. based systems,2014,67:162-168. [92]YAO Yiyu.Three-way decisions and cognitive computing 「80]桑妍丽,钱宇华.一种悲观多粒度粗糙集中的粒度约简 [J].Cognitive Computation.2016,8(4):543-554. 算法[J].模式识别与人工智能,2012,25(3):361- [93]刘清,邱桃荣,刘斓.基于非标准分析的粒计算研究 366. [J].计算机学报.2015,38(8):1618-1627. SANG Yanli,QIAN Yuhua.A granular space reduction ap- LIU Qing,QIU Taorong,LIU Lan.The research of granu- proach to pessimistic multi-granulation rough sets[.Pat- lar computing based on nonstandard analysis[].Chinesebination granulation in incomplete information system[ J]. Lecture notes in computer science, 2006, 4062: 184-190. [69]WANG Junhong, LIANG Jiye, QIAN Yuhua, et al. Uncer⁃ tainty measure of rough sets based on a knowledge granula⁃ tion for incomplete information systems [ J]. International journal of uncertainty, fuzziness and knowledge⁃based sys⁃ tems, 2008, 16(2): 233-244. [70]梁吉业, 钱宇华. 信息系统中的信息粒与熵理论[ J]. 中国科学 E 辑: 信息科学, 2008, 38(12): 2048-2065. LIANG Jiye, QIAN Yuhua. Information granules and entro⁃ py theory in information systems[J]. Science in China se⁃ ries F: information sciences, 2008, 51(10): 1427-1444. [71]BAYES T. An essay towards solving a problem in the doc⁃ trine of chances[J]. Philosophical transactions of the royal society, 53 (1763): 370-418. [72] YU Jianhang, ZHANG Xiaoyan, ZHAO Zhenhua et al. Uncertainty measures in multigranulation with different grades rough set based on dominance relation[ J]. Journal of intelligent & fuzzy systems, 2016 ,31:1133-1144. [ 73] LIN Guoping, LIANG Jiye, QIAN Yuhua. Uncertainty measures for multigranulation approximation space[J]. In⁃ ternational journal of uncertainty fuzziness and knowledge⁃ based systems, 2015, 23(3) 443-457. [74] ZHANG Qinghua, ZHANG Qiang, WANG Guoyin. The uncertainty of probabilistic rough sets in multi⁃granulation spaces[J]. International journal of approximate reasoning, 2016, 77: 38-54. [75]苗夺谦. Rough Set 理论及其在机器学习中的应用研究 [D]. 1997, 北京,中国科学院自动化研究所. MIAO Duoqian. Rough set theory and its application in ma⁃ chine learning [ D]. 1997, Beijing, Institute of Automa⁃ tion, Chinese Academy of Sciences. [ 76 ] MA Zhouming, MI Jusheng. A comparative study of MGRSs and their uncertainty measures[ J]. Fundamenta informaticae, 2015, 142:161-181. [77]HUANG Bing, GUO Chunxiang, LI Huaxiong, et al. Hier⁃ arhical structures and uncertainty measures for intuitionistic fuzzy approximate space[ J]. Information Sciences, 2016, 336: 92-114. [78]LIANG Jiye, WANG Feng, DANG Chuangyin, et al. An efficient rough feature selection algorithm with a multi⁃ granulation view[ J]. International journal of approximate reasoning, 2012, 53(6): 912-926. [79]LIN Yaojin, LI Jinjin, LI Peirong, et al. Feature selection via neighborhood multi⁃granulation fusion[ J]. Knowledge⁃ based systems, 2014, 67: 162-168. [80]桑妍丽,钱宇华. 一种悲观多粒度粗糙集中的粒度约简 算法[J]. 模式识别与人工智能, 2012, 25(3): 361- 366. SANG Yanli, QIAN Yuhua. A granular space reduction ap⁃ proach to pessimistic multi⁃granulation rough sets[J]. Pat⁃ tern recognition and artificial intelligence, 2012, 25(3): 361-366. [81] SHE Yanhong, LI Jinhai, YANG Hailong. A local ap⁃ proach to rule induction in multi⁃scale decision tables[J]. Knowledge⁃based systems, 2015, 89: 398-410. [82]邓大勇, 徐小玉, 黄厚宽. 基于并行约简的概念漂移探 测[J]. 计算机研究与发展, 2015, 52(5): 1071-1079. DENG Dayong, XU Xiaoyu, HUANG Houkuan. Concept drifting detection for categorical evolving data based on par⁃ allel reducts[J]. Journal of computer research and devel⁃ opment, 2015, 52(5):1071-1079. [83]徐计, 王国胤, 于洪. 基于粒计算的大数据处理[J]. 计 算机学报, 2015, 38(8): 1497-1517. XU Ji, WANG Guoyin, YU Hong. Review of big data pro⁃ cessing based on granular computing[ J]. Chinese journal of computers, 2015, 38(8): 1497-1517. [84]RUAN Junhu, WANG Xuping, SHI Yan. Developing fast predictors for large⁃scale time series using fuzzy granular support vector machines [ J ]. Applied soft computing, 2013, 13(6): 3981-4000. [85]HE Jieyue, ZHONG Wei, HARRISON R, et al. Clustering support vector machines and its application to local protein tertiary structure prediction [ C] / / Proceedings of the 6th International Conference on Computational Science. Read⁃ ing, UK: Springer⁃Verlag, 2006: 710-717. [86]欧阳继红, 刘燕辉, 李熙铭, 等. 基于 LDA 的多粒度主 题情感混合模型[ J]. 电子学报, 2015, 43(9): 1875- 1880. OUYANG Jihong, LIU Yanhui, LI Ximing, et al. Multi⁃ grain sentiment / topic model based on LDA[J]. Acta elec⁃ tronica sinica, 2015, 43(9): 1875-1880. [87]WANG Xuekuan, ZHAO Cairong, MIAO Duoqian, et al. Fusion of multiple channel features for person re⁃identifica⁃ tion[J]. Neurocomputing, 2016, 213: 125-136. [88]XU Weihua, YU Jianhang. A novel approach to information fusion in multi⁃source datasets: a granular computing view⁃ point[J]. Information sciences, 2017, 378: 410-423. [89] LIN Guoping, LIANG Jiye, QIAN Yuhua. et al. A fuzzy multigranulation decision⁃theoretic approach to multisource fuzzy information systems [ J]. Knowledge⁃based systems, 2016, 91: 102-113. [90]http: / / cncc.ccf.org.cn / struct / 7. [91]LI Jinhai, HUANG Chenchen, QI Jianjun et al. Three⁃way cognitive concept learning via multi⁃granularity[ J]. Infor⁃ mation Sciences. 2017, 378 244-263. [92] YAO Yiyu. Three⁃way decisions and cognitive computing [J]. Cognitive Computation. 2016, 8(4): 543-554. [93]刘清, 邱桃荣,刘斓. 基于非标准分析的粒计算研究 [J]. 计算机学报. 2015, 38(8):1618-1627. LIU Qing, QIU Taorong, LIU Lan. The research of granu⁃ lar computing based on nonstandard analysis[ J]. Chinese ·756· 智 能 系 统 学 报 第 11 卷
<<向上翻页向下翻页>>
©2008-现在 cucdc.com 高等教育资讯网 版权所有