We model a three-networked system of frustrated phased oscillators, with each population labelled Blue, Green and Red.
The experimental results show that the latest isolation‐based anomaly detectors, iForest and iNNE, have outstanding performance on this task and have promising applicability as efficient methods for guaranteeing the lead‐acid battery quality and reliability in civil aviation aircraft.
Our survey provides technical details on how different frameworks systematically unify crowdsourcing aspects to determine the response quality.
The theory of Markowitz portfolio has had enormous value and extensive applications in finance since it came into being. A Markowitz model (MM) is taken into consideration for outsourcing to a public cloud in a privacy-conscious way.
We propose to use mass-based dissimilarity, which employs estimates of the probability mass to measure dissimilarity, to replace the distance metric.
We propose a new subspace clustering framework named CSSub (Clustering by Shared Subspaces).
We propose a new measure called Local Contrast, as an alternative to density, to find cluster centers and detect clusters.
With a different isolation mechanism, iNNE has been shown to outperform iForest in terms of detecting local anomalies and tolerance to irrelevant attributes, which becomes obvious in the high‐dimensional data sets.
We propose a new measure called Local Contrast, as an alternative to density, to find cluster centers and detect clusters.