Improved approaches for density-based outlier detection in wireless sensor networks
Density-based algorithms are important data clustering techniques used to find arbitrary
shaped clusters and outliers. Recently, outlier detectors through density-based clustering …
shaped clusters and outliers. Recently, outlier detectors through density-based clustering …
Analysis and detection of diabetes using data mining techniques—a big data application in health care
BM Bai, BM Nalini, J Majumdar - Emerging research in …, 2019 - books.google.com
In digitized world, data is growing exponentially and Big Data Analytics is an emerging trend
and a dominant research field. Data mining techniques play an energetic role in the …
and a dominant research field. Data mining techniques play an energetic role in the …
Deep contrastive clustering for signal deinterleaving
S Yang, X Zhao, H Liu, C Yang, T Peng… - … on Aerospace and …, 2023 - ieeexplore.ieee.org
In a complex electromagnetic environment, radar signal deinterleaving (RSD) is a
challenging task. In this article, a deep contrastive clustering algorithm (DCCA) is advanced …
challenging task. In this article, a deep contrastive clustering algorithm (DCCA) is advanced …
SDN-based dynamic resource management and scheduling for cognitive industrial IoT
S Chandramohan, M Senthilkumaran - International Journal of …, 2022 - emerald.com
Purpose In recent years, it is imperative to establish the structure of manufacturing industry
in the context of smart factory. Due to rising demand for exchange of information with various …
in the context of smart factory. Due to rising demand for exchange of information with various …
[引用][C] An efficient way for clustering using alternative decision tree
E Gothai, P Balasubramanie - American Journal of Applied Sciences, 2012