Abstract Data is the key element that runs the modern society. Large amounts of data are being released day by day as a result of many activities. The digital data is transferred through the Internet which may be vulnerable to attacks while transmitting. Especially, the medical data is observed to be of at most importance.
Rupa Ch +4 more
wiley +1 more source
A comprehensive maternal health risk prediction dataset from IoT-enabled medical cyber-physical systems in developing countries: supporting machine learning and deep learning applications for clinical decision support. [PDF]
Hossain MM, Nayan NM, Kashem MA.
europepmc +1 more source
ABSTRACT Accurately predicting line loss rates is crucial for effective management in distribution networks, particularly for short‐term multihorizon forecasts ranging from 1 hour to 1 week. In this study, we propose attention‐GCN–LSTM, a novel method that integrates graph convolutional networks (GCN), long short‐term memory (LSTM) and a three‐level ...
Jie Liu +4 more
wiley +1 more source
Adjoint propagation of error signal through modular recurrent neural networks for biologically plausible learning. [PDF]
Liu Z +7 more
europepmc +1 more source
ABSTRACT Repetitive motion planning (RMP) for redundant manipulators with high convergent precision becomes an intense research topic due to its more degrees of freedom. In this paper, a specific zeroing neural dynamics (SZND) model for the RMP is first set up via zeroing neurodynamics.
Ying Kong +3 more
wiley +1 more source
A hybrid AI-genetic algorithm framework for the optimization of polymer flooding strategies: a numerical simulation-based approach. [PDF]
Nourizadeh M +3 more
europepmc +1 more source
A Dynamic Correlation‐Information‐Fusion‐Based Spatiotemporal Network for Traffic Flow Forecasting
ABSTRACT Traffic Flow Forecasting (TFF) is a foundational task in the development of Intelligent Transport Systems (ITSs). The primary challenge is to undertake a comprehensive exploration of the intrinsic dynamic spatiotemporal correlations of the road network, unveiling the long‐term evolutionary traffic trends.
Dawen Xia +6 more
wiley +1 more source
The peak shifting electricity consumption management and influencing factors of smart grid from recurrent neural network model and deep learning. [PDF]
Wang F, Huang D, Lu W.
europepmc +1 more source
ABSTRACT Converter transformer vibration failures, primarily because of winding and core vibrations, severely impact the safe operation of high voltage direct current (HVDC) systems. These vibrations are influenced by voltage and current, and are transmitted through transformer oil and structural components to the tank. Current numerical models fail to
Peiyu Jiang, Fanghui Yin, Liming Wang
wiley +1 more source
Air quality estimation from sequential surveillance images using a unified CNN-RNN framework. [PDF]
Wang X, Liu X, Mao W.
europepmc +1 more source

