Predicting user's movement path in indoor environments using the stacked deep learning method and the fuzzy soft-max classifier

Predicting user's movement path in indoor environments using the stacked deep learning method and the fuzzy soft-max classifier

Accurate prediction of a user's movement path has various advantages for many applications, such as optimising a nurse's trajectory in a hospital and assisting elderly or disabled people and making them feel secure and protected in the places where they live. Recently, researchers have sug...

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Bibliographic Details
Main Authors: Bourjandi, M. (Author), GolsorkhtabariAmiri, M. (Author), Yadollahzadeh-Tabari, M. (Author)
Format: Article
Language:English
Published: John Wiley and Sons Inc 2022
Subjects:
Accurate prediction
Brain
Convolution
convolutional neural network
Convolutional neural network
Convolutional neural networks
Data mining
Disabled people
Elderly people
Forecasting
Fuzzy inference
Fuzzy neural networks
fuzzy soft-max classifier
Fuzzy soft-max classifier
Gaussian noise (electronic)
Indoor environment
Learning methods
long short-term memory
Long short-term memory
Motion estimation
Time dependency
User movement
User movement path
user's movement path
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