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Cyber-Physical Systems Virtual Organization
Read-only archive of site from September 29, 2023.
CPS-VO
feedforward neural nets
biblio
Estimating the Number of Hidden Nodes of the Single-Hidden-Layer Feedforward Neural Networks
Submitted by grigby1 on Fri, 07/03/2020 - 4:54pm
hidden nodes
Training data
Training
singular value decomposition
single-hidden-layer feedforward neural network
sample-based data normalization
pubcrawl
optimal number
normalized data
Metrics
Artificial Neural Networks
Feedforward neural networks
feedforward neural nets
Eigenvalues and eigenfunctions
decomposition
data normalization
cyber physical systems
computer architecture
Compositionality
attribute-based data normalization
biblio
Word Embedding Method of SMS Messages for Spam Message Filtering
Submitted by aekwall on Mon, 05/18/2020 - 10:55am
SMS Filtering
machine learning method
classification methods
binary classification
CBOW
deep learning method
feedforward neural network
Feedforward neural networks
popular machine learning method
deep learning
SMS messages
spam message filtering
SVM light
word embedding
word embedding method
word embedding technique
Word Vector
security of data
feedforward neural nets
natural language processing
information filtering
Filtering
electronic messaging
SVM
unsolicited e-mail
pattern classification
pubcrawl
Human behavior
Resiliency
learning (artificial intelligence)
feature extraction
Support vector machines
Scalability
biblio
Multiple Fault Diagnosis of Electric Powertrains Under Variable Speeds Using Convolutional Neural Networks
Submitted by aekwall on Mon, 05/18/2020 - 10:48am
Mechanical power transmission
bearings
electric powertrains
electrical fault detection
electromechanical systems
fault diagnosis methods
Gears
Induction motors
mechanical engineering computing
fault diagnosis
multiple fault diagnosis
power availability
power transmission (mechanical)
Spectrogram
Stator windings
variable speed operations
variable speeds
learning (artificial intelligence)
Electric Vehicles
Vibrations
system reliability
Human Factors
feedforward neural nets
convolution
power engineering computing
convolutional neural networks
cyber physical systems
convolutional neural network
Training
Metrics
deep learning
pubcrawl
Resiliency
biblio
Deep Learning-Based Intrusion Detection for IoT Networks
Submitted by grigby1 on Fri, 05/15/2020 - 11:36am
pubcrawl
IoT devices
IoT network
learning (artificial intelligence)
multiclass classification
Network reconnaissance
packet level
pattern classification
Power Grid
IoT dataset
reconnaissance attacks
resilience
Resiliency
Scalability
security controls
telecommunication traffic
Traffic flow
feed-forward neural networks model
communication infrastructure
computer network security
computing infrastructure
deep learning-based intrusion detection
defence networks
Denial of Service attacks
distributed denial of service
Feed Forward Neural Networks
binary classification
feedforward neural nets
field information
healthcare automation
information theft attacks
Internet of Thing
Internet of Things
Intrusion Detection
biblio
Performance Comparison of Intrusion Detection System Between Deep Belief Network (DBN)Algorithm and State Preserving Extreme Learning Machine (SPELM) Algorithm
Submitted by aekwall on Mon, 05/11/2020 - 11:18am
pedestrian detection
machine learning algorithms
machine learning classifier
Metrics
network intrusion detection
NSL- KDD dataset
NSL-KDD dataset
object detection
pattern classification
learning (artificial intelligence)
pedestrians
security of data
SPELM algorithm
state preserving extreme learning machine algorithm
State Preserving Extreme Learning Machine(SPELM)
testing
Training
DBN algorithm
pubcrawl
composability
Resiliency
Anomaly Detection
Classification algorithms
Computational modeling
cyber security
Data models
belief networks
Deep Belief Network
deep belief network algorithm
face recognition
feature extraction
feedforward neural nets
Intrusion Detection
intrusion detection system
biblio
An Intrusion Detection System using Opposition based Particle Swarm Optimization Algorithm and PNN
Submitted by aekwall on Mon, 01/27/2020 - 10:26am
probability
Probabilistic Neural Network
OPSO
NSL KDD dataset
intrusion detection models
IDS model
feedforward neural net algorithms
Feed Forward Network
artificial neural network
ANN
NSL-KDD dataset
Compositionality
feedforward neural nets
Biological neural networks
Artificial Neural Networks
security of data
Intrusion Detection
Feeds
Neurons
Swarm Intelligence
particle swarm optimization algorithm
particle swarm optimization
particle swarm optimisation
Computational modeling
composability
pubcrawl
learning (artificial intelligence)
network security
intrusion detection system
biblio
Is Predicting Software Security Bugs Using Deep Learning Better Than the Traditional Machine Learning Algorithms?
Submitted by aekwall on Mon, 07/01/2019 - 10:14am
Predictive models
Support vector machines
software security bugs
software quality metrics
software quality
software metrics
software insecurity
Software
security-related bugs
security of data
Security Metrics
security breaches
security
Random Forest
pubcrawl
program debugging
predictive security metrics
Naive Bayes
multilayer deep feedforward network
Metrics
machine learning
learning (artificial intelligence)
feedforward neural nets
Feedforward Artificial Network
deep learning technique
deep learning
Decision trees
Decision Tree
Computer bugs
Bug Propensity Correlational Analysis
Bayes methods
biblio
Classifying Malware Using Convolutional Gated Neural Network
Submitted by grigby1 on Mon, 06/10/2019 - 2:01pm
malware classification
Task Analysis
Resiliency
resilience
Recurrent neural networks
recurrent neural nets
pubcrawl
privacy
pattern classification
neural network
microsoft malware classification challenge
Metrics
malware detection
CNN
malware
malicious software
machine learning
Logic gates
invasive software
information technology society
Human behavior
Gated Recurrent Unit
feedforward neural nets
Deep Neural Network
convolutional neural networks
convolutional gated recurrent neural network model
biblio
Malware Classification with Deep Convolutional Neural Networks
Submitted by grigby1 on Mon, 06/10/2019 - 2:01pm
learning (artificial intelligence)
Support vector machines
Resiliency
resilience
pubcrawl
privacy
Microsoft malware
Metrics
malware classification
malware binaries
malware
Malimg malware
machine learning approaches
machine learning
Learning systems
challenging malware classification datasets
invasive software
image classification
Human behavior
grayscale images
Gray-scale
feedforward neural nets
deep learning framework
deep learning approach
deep learning
deep convolutional neural networks
convolutional neural networks
convolution
computer architecture
CNN
biblio
Effective Botnet Detection Through Neural Networks on Convolutional Features
Submitted by grigby1 on Fri, 04/05/2019 - 10:23am
invasive software
Training
telecommunication traffic
Servers
Resiliency
resilience
pubcrawl
Peer-to-peer computing
Payloads
P2P botnet datasets
Neural networks
Network traffic classification
Metrics
machine learning
learning (artificial intelligence)
IP networks
botnet
internet
feedforward neural nets
feed-forward artificial neural network
feature extraction
DDoS Attacks
cybercrimes
convolutional neural networks
convolutional features
convolution
computer network security
Computer crime
Compositionality
botnets
botnet detection system
Botnet detection
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