State of charge estimation of lithium-ion batteries using LSTM and NARX neural networks
Highly accurate state of charge (SOC) estimation of lithium-ion batteries is one of the key
technologies of battery management systems in electric vehicles. The performance of SOC …
technologies of battery management systems in electric vehicles. The performance of SOC …
State of charge estimation for lithium-ion batteries using dynamic neural network based on sine cosine algorithm
State of charge (SOC) of the lithium-ion batteries is one of the key parameters of the battery
management system, which the performance of SOC estimation guarantees energy …
management system, which the performance of SOC estimation guarantees energy …
Learning the dynamics of realistic models of C. elegans nervous system with recurrent neural networks
Given the inherent complexity of the human nervous system, insight into the dynamics of
brain activity can be gained from studying smaller and simpler organisms. While some of the …
brain activity can be gained from studying smaller and simpler organisms. While some of the …
An Economic Analysis of Energy Consumption at Student Residences in a South African-Based Academic Institution Using NARX Neural Network
One of the issues associated with the supply of electricity is its generation capacity, and this
has led to prevalent power cuts and high costs of usage experienced in many developing …
has led to prevalent power cuts and high costs of usage experienced in many developing …
Dynamic model development for vehicle air conditioners based on physics-guided deep learning
Air conditioners (AC) are responsible for the largest portion of energy use among all
auxiliary components of vehicles. Most white-box models developed for dynamic modeling …
auxiliary components of vehicles. Most white-box models developed for dynamic modeling …
Battery energy storage control systems and methods for a grid tie inverter coupled to a photovoltaic system
A distributed control system uses a central controller in Internet communication with a local
controller to manage grid tie attachment with a battery to form an integrated battery energy …
controller to manage grid tie attachment with a battery to form an integrated battery energy …
Efficient data aggregation technique for medical wireless body sensor networks
M Belhaj Mohamed, A Meddeb-Makhlouf… - tm-Technisches …, 2022 - degruyter.com
A central issue in Wireless Body Sensor Networks (WBSNs) is the large amount of
measurement data for monitoring vital parameters, which need to be continuously …
measurement data for monitoring vital parameters, which need to be continuously …
Optimizing narx-rnn performance to predict precious metal futures market
Precious metals offer lucrative investments appealing to investors globally, leading to a
surge in demand for accurate forecasts. Published literature for prediction applications often …
surge in demand for accurate forecasts. Published literature for prediction applications often …
A combined neural network model for forecasting solar energy from multiple weather parameters
KP Nguyen, CH Hoang, HQ Minh - … International Symposium on …, 2023 - ieeexplore.ieee.org
The article aims to propose a combined neural network model to forecast the solar energy of
a solar power plant. Predicting solar energy is extremely important in planning, investing in …
a solar power plant. Predicting solar energy is extremely important in planning, investing in …
Modelling Neuronal Behaviour with Time Series Regression: Recurrent Neural Networks on C. Elegans Data
G Mestre, R Barbulescu, AL Oliveira… - arXiv preprint arXiv …, 2021 - arxiv.org
Given the inner complexity of the human nervous system, insight into the dynamics of brain
activity can be gained from understanding smaller and simpler organisms, such as the …
activity can be gained from understanding smaller and simpler organisms, such as the …