An autocorrelation incremental fuzzy clustering framework based on dynamic conditional scoring model
Y Zhang, X Li, L Wang, S Fan, L Zhu, S Jiang - Information Sciences, 2023 - Elsevier
This paper focuses on the real-time dynamic clustering analysis of power load data based
on the dynamic conditional score (DCS) model, and an autocorrelation increment fuzzy C …
on the dynamic conditional score (DCS) model, and an autocorrelation increment fuzzy C …
Modified total Bregman divergence driven picture fuzzy clustering with local information for brain MRI image segmentation
H Lohit, D Kumar - Applied Soft Computing, 2023 - Elsevier
This research work discusses a noise-robust picture fuzzy clustering method with an
application to the MRI image segmentation problem. The MRI images suffer from the …
application to the MRI image segmentation problem. The MRI images suffer from the …
Improved interval type-2 fuzzy K-means clustering based on adaptive iterative center with new defuzzification method
X Zhang, T Zhang, Y Zhang, F Ma - International Journal of Approximate …, 2023 - Elsevier
Abstract Interval Type-2 Fuzzy K-means (IT2FKM) is an efficient clustering algorithm, which
mainly focuses on further describes the uncertainty of the data sets by introducing interval …
mainly focuses on further describes the uncertainty of the data sets by introducing interval …
An equidistance index intuitionistic fuzzy c-means clustering algorithm based on local density and membership degree boundary
Q Ma, X Zhu, X Zhao, B Zhao, G Fu, R Zhang - Applied Intelligence, 2024 - Springer
Fuzzy c-means (FCM) algorithm is an unsupervised clustering algorithm that effectively
expresses complex real world information by integrating fuzzy parameters. Due to its …
expresses complex real world information by integrating fuzzy parameters. Due to its …
Multi-homed abnormal behavior detection algorithm based on fuzzy particle swarm cluster in user and entity behavior analytics
J Cui, G Zhang, Z Chen, N Yu - Scientific Reports, 2022 - nature.com
User and entity behavior analytics (UEBA) is an anomaly detection technique that identifies
potential threat events in the enterprise's internal threat analysis and external intrusion …
potential threat events in the enterprise's internal threat analysis and external intrusion …
Improved harris combined with clustering algorithm for data traffic classification
Q Liu, M Li, N Cao, Z Zhang, G Yang - IEEE Access, 2022 - ieeexplore.ieee.org
Aiming at the problem that the data traffic in the intelligent wireless communication system
presents complex characteristics such as burstiness and self-similarity, which leads to the …
presents complex characteristics such as burstiness and self-similarity, which leads to the …
Research on long term power load grey combination forecasting based on fuzzy support vector machine
Y Chen, C Xiao, S Yang, Y Yang, W Wang - Computers and Electrical …, 2024 - Elsevier
Aiming at the problem of low accuracy of single model in power load forecasting, a method
based on fuzzy support vector machine and grey combination forecasting is proposed. The …
based on fuzzy support vector machine and grey combination forecasting is proposed. The …
Discriminative projection fuzzy K-Means with adaptive neighbors
Abstract Fuzzy K-Means (FKM) based on fuzzy theory is a classic method to effectively
handle overlapping regions between clusters. However, redundant features and noises …
handle overlapping regions between clusters. However, redundant features and noises …
An enhanced energy and distance based optimized clustering and dynamic adaptive cluster-based routing in software defined vehicular network
A Sajithabegam, T Menakadevi - Telecommunication Systems, 2024 - Springer
Abstract Software-Defined Vehicular Networks (SDVN) have been established to facilitate
secure and adaptable vehicle communication within the dynamic environment of Vehicular …
secure and adaptable vehicle communication within the dynamic environment of Vehicular …
Revisiting Possibilistic Fuzzy C-Means Clustering Using the Majorization-Minimization Method
Y Chen, S Zhou - Entropy, 2024 - search.proquest.com
Possibilistic fuzzy c-means (PFCM) clustering is a kind of hybrid clustering method based on
fuzzy c-means (FCM) and possibilistic c-means (PCM), which not only has the stability of …
fuzzy c-means (FCM) and possibilistic c-means (PCM), which not only has the stability of …