Predicting Human Behaviour with Recurrent Neural Networks
As the average age of the urban population increases, cities must adapt to improve the quality of life of their citizens. The City4Age H2020 project is working on the early detection of the risks related to mild cognitive impairment and frailty and on providing meaningful interventions that prevent...
Main Authors: | Aitor Almeida, Gorka Azkune |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-02-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | http://www.mdpi.com/2076-3417/8/2/305 |
Similar Items
-
A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network
by: Xiaofang Pan, et al.
Published: (2019-01-01) -
Predicting Vehicle Behavior Using Automotive Radar and Recurrent Neural Networks
by: Saptarshi Mukherjee, et al.
Published: (2021-01-01) -
Production prediction at ultra-high water cut stage via Recurrent Neural Network
by: Hongliang WANG, et al.
Published: (2020-10-01) -
Improving Financial Time Series Prediction Accuracy Using Ensemble Empirical Mode Decomposition and Recurrent Neural Networks
by: Henry Daniel Chacon, et al.
Published: (2020-01-01) -
Highway Speed Prediction Using Gated Recurrent Unit Neural Networks
by: Myeong-Hun Jeong, et al.
Published: (2021-03-01)