Computer Science ›› 2025, Vol. 52 ›› Issue (11A): 241200110-7.doi: 10.11896/jsjkx.241200110
• Big Data & Data Science • Previous Articles Next Articles
WU Shaohua1, CHEN Yuming2
CLC Number:
| [1]ZADEH L A.Fuzzy sets and information granularity [J].Fuzzy Sets,Fuzzy Logic,and Fuzzy Systems,1996,8:433-448. [2]WANG G Y,ZHANG Q H,HU J.An overview of granularcomputing [J].CAAI Transactions on Intelligent Systems,2016,29(6):927-933. [3]LIN T Y.Granular computing on binary relations I:data mining and neighborhood systems [J].Rough Sets in Knowledge Discovery,1998,1(1):107-121. [4]XUE R X,YI S C,WANG P X.GBDEN:a fast clustering algorithm for large-scale data based on granular ball [J].Computer Science,2024,12:166-173. [5]MIAO D Q,WANG J.On the relationships between information entropy and roughness of knowledge in rough set theory [J].PR & AI,1998,11(1):34-40. [6]MIAO D Q,WANG J.An information representation of the concepts and operations in rough set theory [J].Journal of Software,1999,10(2):113-116. [7]MIAO D Q,ZHANG Q H,et al.From human intelligence to machine implementation model:theories and applications based on granular computing [J].CAAI Transactions on Intelligent Systems,2016,11(6):743-757. [8]YAO Y Y.Granular computing using neighborhood systems[M]//Advances in Soft Computing:Engineering Design and Manufacturing.London:Springer,1999:539-553. [9]PEDRYCZ W.Granular computing for data analytics:a manifesto of human-centric computing [J].IEEE/CAA Journal of Automatica Sinica,2018,5(6):1025-1034. [10]MIAO D Q,FAN S D.The calculation of knowledge granulation and its application [J].Systems Engineering－Theory & Practice,2002,22(1):48-56. [11]HU Q H,YU D R,XIE Z X.Numerical attribute reduction based on neighborhood granulation and rough approximation [J].Journal of Software,2008,19(3):640-649. [12]CHEN Y M,ZHU S Z,LI W,et al.Fuzzy granular convolutional classifiers [J].Fuzzy Sets and Systems,2022,426:145-162. [13]CHEN Y M,QIN N,LI W,et al.Granule structures,distances and measures in neighborhood systems [J].Knowledge-Based Systems,2019,165:268-281. [14]ZHENG C Y,CHEN Y Y,HOU X Y,et al.A neighbourhood granular fuzzy c-means clustering algorithm [J].Journal of Shandong University(Natural Science),2024,59(5):35-44. [15]ROSENBLATT F.The perception:a probabilistic model for information storage and organization in the Brain [J].Psychological Review,1958,65(6):111-127. [16]LI W,YANG H.A non-linear blind source separation method based on perceptron structure and conjugate gradient algorithm[J].Circuits,Systems,and Signal Process,2014,33:3573-3590. [17]XU J H,ZHANG X G,LI Y D.A nonlinear perceptron algo-rithm based on kernel functions [J].Chinese Journal of Compu-ters,2002,25(7):689-695. [18]CHOLAQUIDIS A,FRAIMAN R,KALEMKERIAN J,et al.A nonlinear aggregation type classifier [J].Jounal of Multivariate Analysis,2016,146:269-281. [19]NIE F P,ZHU W,LI X L.Decision tree svm:an extension oflinear svm for non-linear classification [J].Neurocomputing,2020,401:153-159. [20]KWAK N.Nonlinear projection trick in kernel methods:an alternative to the kernel trick [J].IEEE Transactions on Neural Networks and Learning Systems,2013,24(12):2113-2119. [21]KEMPFER K C,WANG Y,et al.A comparison study on nonli-near dimension reduction methods with kernel variations:visua-lization,optimization and classification [J].Intelligent Data Analysis,2020,24(2):267-290. [22]FU X Y,CHEN Y Y,CHEN Y M,et al.A classification method of fully connected granular neural network [J].Journal of Shanxi University(Natural Science Edition),2023,46(1):91-100. [23]YANG T,ZHONG X R,LANG G M,et al.Granular matrix:a new approach for granular structure reduction and redundancy evaluation [J],IEEE Transactions on Fuzzy Systems,2020,28(12):3133-3144. [24]LIU W X,LI J J,WANG H W.A dynamic attribute reduction method for formal context based on matrix information entropy [J].Journal of Nanjing University(Natural Science),2025,61(1):117-128. |
|
||
Home