Matches in SemOpenAlex for { <https://semopenalex.org/work/W4383333830> ?p ?o ?g. }
Showing items 1 to 72 of
72
with 100 items per page.
- W4383333830 abstract "K-means algorithm is a typical distance-based clustering analysis algorithm, and the neighborhood granular K-means clustering algorithm uses the neighborhood granulation technique on its basis to solve the problem of poor clustering of the K-means clustering algorithm on non-linear separable datasets. However, the use of neighborhood relations in the granulation lead to the inability of the algorithm to deal with outliers effectively, resulting in some samples being misclassified. By introducing the concept of fuzzy set and combining granular computing theory, a new neighborhood granular K-means clustering method is proposed, where samples are constructed using fuzzy neighborhood granularity technique to construct fuzzy neighborhood granules, and the membership between samples is used for neighborhood granularity instead of clear neighborhood relations, which reduces the impact of outliers. A new distance measure for fuzzy neighborhood granules is proposed based on the size and form of the fuzzy neighborhood granules, which reduces the computational complexity. In addition, the algorithm combines the idea of K Nearest Neighbor to define a neighborhood threshold metric that adaptively generates neighborhood thresholds for any data set. It considers the size of the data set objectively and reduces the subjective influence of manual selection of neighborhood threshold. Finally, the Accuracy and Fowlkes Mallows Index values of the algorithm are increased by 6.4 %, 9.21%, 3.5%, and 7.89% on the synthetic data set and UCI data set, respectively, and increased by 8.65% and 9.43% on the seismic facies lithology identification data set, respectively. The experimental results prove the feasibility and effectiveness of the fuzzy neighborhood granular K-means clustering method." @default.
- W4383333830 created "2023-07-07" @default.
- W4383333830 creator A5006422020 @default.
- W4383333830 creator A5022062543 @default.
- W4383333830 creator A5033300763 @default.
- W4383333830 creator A5052226015 @default.
- W4383333830 creator A5066265467 @default.
- W4383333830 date "2023-05-26" @default.
- W4383333830 modified "2023-09-26" @default.
- W4383333830 title "A K-means Clustering Method for Fuzzy Neighborhood Granules" @default.
- W4383333830 cites W1995450389 @default.
- W4383333830 cites W2018861434 @default.
- W4383333830 cites W2036313261 @default.
- W4383333830 cites W2120688485 @default.
- W4383333830 cites W2125687218 @default.
- W4383333830 cites W2268194897 @default.
- W4383333830 cites W2903476567 @default.
- W4383333830 cites W2912707296 @default.
- W4383333830 cites W2916855271 @default.
- W4383333830 cites W2972155310 @default.
- W4383333830 cites W3046676927 @default.
- W4383333830 cites W4211007335 @default.
- W4383333830 doi "https://doi.org/10.1109/iciba56860.2023.10164929" @default.
- W4383333830 hasPublicationYear "2023" @default.
- W4383333830 type Work @default.
- W4383333830 citedByCount "0" @default.
- W4383333830 crossrefType "proceedings-article" @default.
- W4383333830 hasAuthorship W4383333830A5006422020 @default.
- W4383333830 hasAuthorship W4383333830A5022062543 @default.
- W4383333830 hasAuthorship W4383333830A5033300763 @default.
- W4383333830 hasAuthorship W4383333830A5052226015 @default.
- W4383333830 hasAuthorship W4383333830A5066265467 @default.
- W4383333830 hasConcept C11413529 @default.
- W4383333830 hasConcept C124101348 @default.
- W4383333830 hasConcept C153180895 @default.
- W4383333830 hasConcept C154945302 @default.
- W4383333830 hasConcept C17212007 @default.
- W4383333830 hasConcept C33704608 @default.
- W4383333830 hasConcept C33923547 @default.
- W4383333830 hasConcept C41008148 @default.
- W4383333830 hasConcept C42011625 @default.
- W4383333830 hasConcept C58166 @default.
- W4383333830 hasConcept C73555534 @default.
- W4383333830 hasConcept C79337645 @default.
- W4383333830 hasConceptScore W4383333830C11413529 @default.
- W4383333830 hasConceptScore W4383333830C124101348 @default.
- W4383333830 hasConceptScore W4383333830C153180895 @default.
- W4383333830 hasConceptScore W4383333830C154945302 @default.
- W4383333830 hasConceptScore W4383333830C17212007 @default.
- W4383333830 hasConceptScore W4383333830C33704608 @default.
- W4383333830 hasConceptScore W4383333830C33923547 @default.
- W4383333830 hasConceptScore W4383333830C41008148 @default.
- W4383333830 hasConceptScore W4383333830C42011625 @default.
- W4383333830 hasConceptScore W4383333830C58166 @default.
- W4383333830 hasConceptScore W4383333830C73555534 @default.
- W4383333830 hasConceptScore W4383333830C79337645 @default.
- W4383333830 hasLocation W43833338301 @default.
- W4383333830 hasOpenAccess W4383333830 @default.
- W4383333830 hasPrimaryLocation W43833338301 @default.
- W4383333830 hasRelatedWork W2165254090 @default.
- W4383333830 hasRelatedWork W2165695836 @default.
- W4383333830 hasRelatedWork W2343149624 @default.
- W4383333830 hasRelatedWork W2390188950 @default.
- W4383333830 hasRelatedWork W2518466227 @default.
- W4383333830 hasRelatedWork W2611432661 @default.
- W4383333830 hasRelatedWork W2783242366 @default.
- W4383333830 hasRelatedWork W4312609022 @default.
- W4383333830 hasRelatedWork W4313069709 @default.
- W4383333830 hasRelatedWork W122234192 @default.
- W4383333830 isParatext "false" @default.
- W4383333830 isRetracted "false" @default.
- W4383333830 workType "article" @default.