A review of current machine learning approaches for anomaly detection in network traffic
WA Ali, KN Manasa, M Bendechache… - … and the Digital …, 2020 - search.informit.org
Due to the advance in network technologies, the number of network users is growing rapidly,
which leads to the generation of large network traffic data. This large network traffic data is …
which leads to the generation of large network traffic data. This large network traffic data is …
Prediction of dissolved oxygen in pond culture water based on K-means clustering and gated recurrent unit neural network
X Cao, Y Liu, J Wang, C Liu, Q Duan - Aquacultural Engineering, 2020 - Elsevier
Dissolved oxygen in water is an important ecological factor in ensuring the healthy growth of
aquatic products, as hypoxic stress is known to restrict the growth of aquatic products. The …
aquatic products, as hypoxic stress is known to restrict the growth of aquatic products. The …
An entropy-based initialization method of K-means clustering on the optimal number of clusters
Clustering is an unsupervised learning approach used to group similar features using
specific mathematical criteria. This mathematical criterion is known as the objective function …
specific mathematical criteria. This mathematical criterion is known as the objective function …
Use of clustering to reduce the number of different setting groups for adaptive coordination of overcurrent relays
M Ojaghi, V Mohammadi - IEEE Transactions on Power …, 2017 - ieeexplore.ieee.org
The facility to save multiple setting groups (SGs) within digital overcurrent relays (OCRs) is
to adapt the active setting of the relays to the current topology of the power network …
to adapt the active setting of the relays to the current topology of the power network …
Enhancement clustering evaluation result of davies-bouldin index with determining initial centroid of k-means algorithm
B Jumadi Dehotman Sitompul… - Journal of Physics …, 2019 - iopscience.iop.org
K-Means is one of the most popular clustering algorithms because it is easy and simple
when implemented. However, clustering results from K-Means are very sensitive to the …
when implemented. However, clustering results from K-Means are very sensitive to the …
Clustering analysis using an adaptive fused distance
The selection of a proper distance function is crucial for analyzing the data efficiently. To find
an appropriate distance for clustering algorithm is an unsolved problem as of now. The …
an appropriate distance for clustering algorithm is an unsolved problem as of now. The …
Quantum k-means algorithm based on Manhattan distance
Z Wu, T Song, Y Zhang - Quantum Information Processing, 2022 - Springer
Traditional k-means algorithm measures the Euclidean distance between any two data
points, but it is not applicable in many scenarios, such as the path information between two …
points, but it is not applicable in many scenarios, such as the path information between two …
Implementasi k-Means Clustering untuk Analisis Nilai Akademik Siswa Berdasarkan Nilai Pengetahuan dan Keterampilan
DO Dacwanda, Y Nataliani - Aiti, 2021 - ejournal.uksw.edu
Student success is a reflection of the quality of education. The quality and student
performance need to be improved through educational facilities, infrastructure, and human …
performance need to be improved through educational facilities, infrastructure, and human …
[HTML][HTML] Quantum clustering with k-means: A hybrid approach
Quantum computing, based on quantum theory, holds great promise as an advanced
computational paradigm for achieving fast computations. Quantum algorithms are expected …
computational paradigm for achieving fast computations. Quantum algorithms are expected …
Using unsupervised machine learning techniques for behavioral-based credit card users segmentation in Africa
E Umuhoza, D Ntirushwamaboko… - SAIEE Africa …, 2020 - ieeexplore.ieee.org
Given the fierce competition that has come up because of evolving FinTech and e-payment
industries in the global market, the credit card industry has become extremely competitive …
industries in the global market, the credit card industry has become extremely competitive …