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Cyber-Physical Systems Virtual Organization
Fostering collaboration among CPS professionals in academia, government, and industry
CPS-VO
k nearest neighbor
biblio
Fraud Detection using Machine Learning and Deep Learning
Submitted by aekwall on Mon, 08/24/2020 - 1:37pm
Data models
Support vector machines
support vector machine
learning (artificial intelligence)
machine learning
Random Forest
Resiliency
pubcrawl
composability
deep learning
pattern classification
convolutional neural nets
deep learning methods
Data mining
convolutional neural networks
Artificial Neural Networks
belief networks
fraud
fraud detection
financial data processing
Europe
Forestry
Credit cards
area under the ROC curve
Australian dataset
autoencoder
benchmark multiple machine learning methods
Boltzmann machines
cost of failure
credit card
data mining techniques
Deep belief networks
EU
European dataset
German dataset
k nearest neighbor
Matthews correlation coefficient
restricted boltzmann machine
security checks
biblio
Machine Learning-Based Recommendation Trust Model for Machine-to-Machine Communication
Submitted by grigby1 on Mon, 06/10/2019 - 1:56pm
Bayes methods
composability
Computational modeling
computer network security
Decision Tree
Decision trees
internet
Internet of Things(IoTs)
Internet of Vehicles(IoVs)
Internet Protocol
k nearest neighbor
learning (artificial intelligence)
machine learning
machine learning trust evaluation
Machine learning-based recommendation trust model
Machine Type Communication Devices
Machine-to-Machine communication nodes
machine-to-machine communications
Machine-to-Machine(M2M)
malicious data
Mathematical model
Naive Bayes
pattern classification
Peer-to-peer computing
privacy
pubcrawl
radial support vector machine
Random Forest
receiver operating characteristics
Reliability
resilience
Resiliency
security
security issues
security threats
Supervisory Control and Data Supervisory Acquisition(SCADA)
Support vector machines
telecommunication computing
trust computation measures
Trusted Computing
