FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3213120267> ?p ?o ?g. }

• W3213120267 endingPage "116153" @default.
• W3213120267 startingPage "116153" @default.
• W3213120267 abstract "Real-world data are often corrupted by noise and outliers, which are originated from different procedures such as data collection, storage, and processing. Noise and outliers decrease the quality of clustering and lead to the inaccurate and misplaced cluster centers. In this paper, we propose a new algorithm called Improved Possibilistic Fuzzy C-Means (IPFCM) to cluster noisy data. First, initial cluster centers are calculated by Possibilistic Fuzzy C-Means (PFCM) which do not match dense regions of the data. Then, the domain is divided to some subdomains and each data point is assigned to a sub-domain. The cluster centers are iteratively moved towards high-density regions by maximizing a novel cluster validity index. In the proposed method, a Gaussian membership function is defined on each cluster to weight the data. Then, the sum of weights in each cluster is calculated. The product of these values is considered as the validity index. Since division of the domain is changed with moving the cluster centers, this procedure is repeated until the convergent criterion is satisfied. Cluster analysis performed on six synthetics, nine real benchmarks datasets shows the superiority of IPFCM over some previous clustering algorithms such as Fuzzy C-Means (FCM), PFCM, Kernel Fuzzy C-Means (KFCM), Noise Clustering (NC), and Generalized Entropy based Possibilistic Fuzzy C-Means (GEPFCM). The clustering results of near-fault ground motion data indicate that the cluster centers identified by IPFCM are well separated from each other, while those for PFCM are close to each other in some datasets. Moreover, the results show that the impact of noisy data on the proposed index and consequently cluster analysis decreases as the noisy data get away from the cluster centers which is one of the advantages of using IPFCM algorithm." @default.
• W3213120267 created "2021-11-22" @default.
• W3213120267 creator A5020402404 @default.
• W3213120267 creator A5054325288 @default.
• W3213120267 creator A5061619280 @default.
• W3213120267 date "2022-04-01" @default.
• W3213120267 modified "2023-10-01" @default.
• W3213120267 title "A gradient ascent algorithm based on possibilistic fuzzy C-Means for clustering noisy data" @default.
• W3213120267 cites W1973628217 @default.
• W3213120267 cites W1987884713 @default.
• W3213120267 cites W1987971958 @default.
• W3213120267 cites W1990368529 @default.
• W3213120267 cites W1990896565 @default.
• W3213120267 cites W1995450389 @default.
• W3213120267 cites W1996747841 @default.
• W3213120267 cites W1997547316 @default.
• W3213120267 cites W1998854384 @default.
• W3213120267 cites W2006611586 @default.
• W3213120267 cites W2018861434 @default.
• W3213120267 cites W2029074121 @default.
• W3213120267 cites W2050612752 @default.
• W3213120267 cites W2051224630 @default.
• W3213120267 cites W2061843755 @default.
• W3213120267 cites W2093528786 @default.
• W3213120267 cites W2110893990 @default.
• W3213120267 cites W2115250905 @default.
• W3213120267 cites W2120688485 @default.
• W3213120267 cites W2125687218 @default.
• W3213120267 cites W2125836384 @default.
• W3213120267 cites W2151570639 @default.
• W3213120267 cites W2152093129 @default.
• W3213120267 cites W2153653017 @default.
• W3213120267 cites W2166502569 @default.
• W3213120267 cites W2167428023 @default.
• W3213120267 cites W2170938037 @default.
• W3213120267 cites W2177837180 @default.
• W3213120267 cites W2202606538 @default.
• W3213120267 cites W2206460478 @default.
• W3213120267 cites W2231159530 @default.
• W3213120267 cites W2333775478 @default.
• W3213120267 cites W2335509667 @default.
• W3213120267 cites W2402118906 @default.
• W3213120267 cites W2476964288 @default.
• W3213120267 cites W2518887646 @default.
• W3213120267 cites W2557513159 @default.
• W3213120267 cites W2567942285 @default.
• W3213120267 cites W2584371520 @default.
• W3213120267 cites W2607232397 @default.
• W3213120267 cites W2607943834 @default.
• W3213120267 cites W2729756742 @default.
• W3213120267 cites W2737636713 @default.
• W3213120267 cites W2754151845 @default.
• W3213120267 cites W2759216810 @default.
• W3213120267 cites W2770121225 @default.
• W3213120267 cites W2770794522 @default.
• W3213120267 cites W2811137829 @default.
• W3213120267 cites W2892567774 @default.
• W3213120267 cites W2898793613 @default.
• W3213120267 cites W2964070360 @default.
• W3213120267 cites W3012210731 @default.
• W3213120267 cites W3012906438 @default.
• W3213120267 cites W3045991771 @default.
• W3213120267 cites W3048705786 @default.
• W3213120267 cites W3192293428 @default.
• W3213120267 doi "https://doi.org/10.1016/j.eswa.2021.116153" @default.
• W3213120267 hasPublicationYear "2022" @default.
• W3213120267 type Work @default.
• W3213120267 sameAs 3213120267 @default.
• W3213120267 citedByCount "5" @default.
• W3213120267 countsByYear W32131202672022 @default.
• W3213120267 countsByYear W32131202672023 @default.
• W3213120267 crossrefType "journal-article" @default.
• W3213120267 hasAuthorship W3213120267A5020402404 @default.
• W3213120267 hasAuthorship W3213120267A5054325288 @default.
• W3213120267 hasAuthorship W3213120267A5061619280 @default.
• W3213120267 hasConcept C11413529 @default.
• W3213120267 hasConcept C115328559 @default.
• W3213120267 hasConcept C124101348 @default.
• W3213120267 hasConcept C153180895 @default.
• W3213120267 hasConcept C154945302 @default.
• W3213120267 hasConcept C164866538 @default.
• W3213120267 hasConcept C17212007 @default.
• W3213120267 hasConcept C199360897 @default.
• W3213120267 hasConcept C33704608 @default.
• W3213120267 hasConcept C33923547 @default.
• W3213120267 hasConcept C41008148 @default.
• W3213120267 hasConcept C44859942 @default.
• W3213120267 hasConcept C58166 @default.
• W3213120267 hasConcept C73555534 @default.
• W3213120267 hasConcept C79337645 @default.
• W3213120267 hasConceptScore W3213120267C11413529 @default.
• W3213120267 hasConceptScore W3213120267C115328559 @default.
• W3213120267 hasConceptScore W3213120267C124101348 @default.
• W3213120267 hasConceptScore W3213120267C153180895 @default.
• W3213120267 hasConceptScore W3213120267C154945302 @default.
• W3213120267 hasConceptScore W3213120267C164866538 @default.
• W3213120267 hasConceptScore W3213120267C17212007 @default.
• W3213120267 hasConceptScore W3213120267C199360897 @default.

• next