Application of Machine Learning and Data Mining

The following special issue contains 14 articles accepted and published in the Special Issue "Mathematics and Computer Science, 2024" of the MDPI journal Mathematics. The included articles cover a wide range of topics related to the theory and applications of Machine Learning and Data Mining, as wel...

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collection Directory of Open Access Books
description The following special issue contains 14 articles accepted and published in the Special Issue "Mathematics and Computer Science, 2024" of the MDPI journal Mathematics. The included articles cover a wide range of topics related to the theory and applications of Machine Learning and Data Mining, as well as their extensions and generalizations. These topics include, but are not limited to, supervised, unsupervised, and self-learning methods; large-scale data mining; applicable neural networks and artificial intelligence; neural network-based industrial applications; neural models for natural language processing; deep learning for health informatics and biomedical engineering; graph convolutional neural networks and their applications; deep reinforcement learning and its applications; deep sparse and low-rank representation; and computer vision and pattern recognition techniques. In addition to these core areas, the authors of the included articles also delve into advanced methodologies and innovative approaches within these fields. The collection aims to provide comprehensive insights into recent advancements and emerging trends in Machine Learning and Data Mining, making it a valuable resource for researchers, practitioners, and students interested in the latest developments in these dynamic disciplines.
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language eng
publishDate 2024
publishDateRange 2024
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publisherStr MDPI - Multidisciplinary Digital Publishing Institute
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spelling doab-20.500.12854ir-1436962024-09-06T08:06:41Z Application of Machine Learning and Data Mining Zhao, Mingbo Zhang, Haijun Wu, Zhou epilepsy detection moth–flame optimization echo state network feature extraction EEG signals machine learning linear regression psychological test mathematical achievement automated guided vehicle task allocation multi-population genetic algorithm particle swarm optimization genetic algorithm voltage stability identification of weak bus FVSI and Lmn diminish power loss PSO variants EPSO foundation model MT-MSTd STDP SNN optic flow denoising autoencoder Bayesian optimization non-intrusive load recognition convolutional neural network greenhouse gases intermodal mathematical optimization multimodal rail/road transportation sustainable transport unimodal defect fixing developer assignment prediction of related issues heterogeneous collaborative network aquaculture adaptive boosting algorithm LSTM combined prediction adversarial machine learning evasion attacks classifier robustness ensemble classifiers gradient correlation mega sports events FIFA World Cup attendee prediction stochastic gradient descent navigation aids state recognition extended space multi-domain features hidden feature extraction maritime safety driving style recognition driving risk field mask learning environmental data safety tips and warnings vehicle-to-everything predictions breakthroughs networks structure dynamics thema EDItEUR::U Computing and Information Technology thema EDItEUR::U Computing and Information Technology::UX Applied computing The following special issue contains 14 articles accepted and published in the Special Issue "Mathematics and Computer Science, 2024" of the MDPI journal Mathematics. The included articles cover a wide range of topics related to the theory and applications of Machine Learning and Data Mining, as well as their extensions and generalizations. These topics include, but are not limited to, supervised, unsupervised, and self-learning methods; large-scale data mining; applicable neural networks and artificial intelligence; neural network-based industrial applications; neural models for natural language processing; deep learning for health informatics and biomedical engineering; graph convolutional neural networks and their applications; deep reinforcement learning and its applications; deep sparse and low-rank representation; and computer vision and pattern recognition techniques. In addition to these core areas, the authors of the included articles also delve into advanced methodologies and innovative approaches within these fields. The collection aims to provide comprehensive insights into recent advancements and emerging trends in Machine Learning and Data Mining, making it a valuable resource for researchers, practitioners, and students interested in the latest developments in these dynamic disciplines. 2024-09-06T08:06:35Z 2024-09-06T08:06:35Z 2024 book ONIX_20240906_9783725819256_58 9783725819256 9783725819263 https://directory.doabooks.org/handle/20.500.12854/143696 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/9716 https://mdpi.com/books/pdfview/book/9716 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-1926-3 10.3390/books978-3-7258-1926-3 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725819256 9783725819263 264 open access
spellingShingle epilepsy detection
moth–flame optimization
echo state network
feature extraction
EEG signals
machine learning
linear regression
psychological test
mathematical achievement
automated guided vehicle
task allocation
multi-population genetic algorithm
particle swarm optimization
genetic algorithm
voltage stability
identification of weak bus
FVSI and Lmn
diminish power loss
PSO variants
EPSO
foundation model
MT-MSTd
STDP
SNN
optic flow
denoising autoencoder
Bayesian optimization
non-intrusive load recognition
convolutional neural network
greenhouse gases
intermodal
mathematical optimization
multimodal
rail/road transportation
sustainable transport
unimodal
defect fixing
developer assignment
prediction of related issues
heterogeneous collaborative network
aquaculture
adaptive boosting algorithm
LSTM
combined prediction
adversarial machine learning
evasion attacks
classifier robustness
ensemble classifiers
gradient correlation
mega sports events
FIFA World Cup
attendee prediction
stochastic gradient descent
navigation aids
state recognition
extended space
multi-domain features
hidden feature extraction
maritime safety
driving style recognition
driving risk field
mask learning
environmental data
safety tips and warnings
vehicle-to-everything
predictions
breakthroughs
networks
structure
dynamics
thema EDItEUR::U Computing and Information Technology
thema EDItEUR::U Computing and Information Technology::UX Applied computing
Application of Machine Learning and Data Mining
title Application of Machine Learning and Data Mining
title_full Application of Machine Learning and Data Mining
title_fullStr Application of Machine Learning and Data Mining
title_full_unstemmed Application of Machine Learning and Data Mining
title_short Application of Machine Learning and Data Mining
title_sort application of machine learning and data mining
topic epilepsy detection
moth–flame optimization
echo state network
feature extraction
EEG signals
machine learning
linear regression
psychological test
mathematical achievement
automated guided vehicle
task allocation
multi-population genetic algorithm
particle swarm optimization
genetic algorithm
voltage stability
identification of weak bus
FVSI and Lmn
diminish power loss
PSO variants
EPSO
foundation model
MT-MSTd
STDP
SNN
optic flow
denoising autoencoder
Bayesian optimization
non-intrusive load recognition
convolutional neural network
greenhouse gases
intermodal
mathematical optimization
multimodal
rail/road transportation
sustainable transport
unimodal
defect fixing
developer assignment
prediction of related issues
heterogeneous collaborative network
aquaculture
adaptive boosting algorithm
LSTM
combined prediction
adversarial machine learning
evasion attacks
classifier robustness
ensemble classifiers
gradient correlation
mega sports events
FIFA World Cup
attendee prediction
stochastic gradient descent
navigation aids
state recognition
extended space
multi-domain features
hidden feature extraction
maritime safety
driving style recognition
driving risk field
mask learning
environmental data
safety tips and warnings
vehicle-to-everything
predictions
breakthroughs
networks
structure
dynamics
thema EDItEUR::U Computing and Information Technology
thema EDItEUR::U Computing and Information Technology::UX Applied computing
topic_facet epilepsy detection
moth–flame optimization
echo state network
feature extraction
EEG signals
machine learning
linear regression
psychological test
mathematical achievement
automated guided vehicle
task allocation
multi-population genetic algorithm
particle swarm optimization
genetic algorithm
voltage stability
identification of weak bus
FVSI and Lmn
diminish power loss
PSO variants
EPSO
foundation model
MT-MSTd
STDP
SNN
optic flow
denoising autoencoder
Bayesian optimization
non-intrusive load recognition
convolutional neural network
greenhouse gases
intermodal
mathematical optimization
multimodal
rail/road transportation
sustainable transport
unimodal
defect fixing
developer assignment
prediction of related issues
heterogeneous collaborative network
aquaculture
adaptive boosting algorithm
LSTM
combined prediction
adversarial machine learning
evasion attacks
classifier robustness
ensemble classifiers
gradient correlation
mega sports events
FIFA World Cup
attendee prediction
stochastic gradient descent
navigation aids
state recognition
extended space
multi-domain features
hidden feature extraction
maritime safety
driving style recognition
driving risk field
mask learning
environmental data
safety tips and warnings
vehicle-to-everything
predictions
breakthroughs
networks
structure
dynamics
thema EDItEUR::U Computing and Information Technology
thema EDItEUR::U Computing and Information Technology::UX Applied computing
url ONIX_20240906_9783725819256_58