Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
A comprehensive review on the state of charge estimation for lithium‐ion battery based on neural network
Implementing carbon neutrality and emission peak policies requires a high‐level electric
vehicle field. Lithium‐ion batteries have been considered an essential component of electric …
vehicle field. Lithium‐ion batteries have been considered an essential component of electric …
Analysis of cyber security attacks and its solutions for the smart grid using machine learning and blockchain methods
Smart grids are rapidly replacing conventional networks on a worldwide scale. A smart grid
has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the …
has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the …
Review on state of charge estimation techniques of lithium-ion batteries: A control-oriented approach
Energy storage has become one of the most critical issues of modern technology. In this
regard, lithium-ion batteries have proven effective as an energy storage option. To optimize …
regard, lithium-ion batteries have proven effective as an energy storage option. To optimize …
Robustness of LSTM neural networks for multi-step forecasting of chaotic time series
Recurrent neurons (and in particular LSTM cells) demonstrated to be efficient when used as
basic blocks to build sequence to sequence architectures, which represent the state-of-the …
basic blocks to build sequence to sequence architectures, which represent the state-of-the …
Detection of false data injection cyber-attacks in DC microgrids based on recurrent neural networks
Cyber-physical systems (CPSs) are vulnerable to cyber-attacks. Nowadays, the detection of
cyber-attacks in microgrids as examples of CPS has become an important topic due to their …
cyber-attacks in microgrids as examples of CPS has become an important topic due to their …
An effective hybrid NARX-LSTM model for point and interval PV power forecasting
This paper proposes an effective Photovoltaic (PV) Power Forecasting (PVPF) technique
based on hierarchical learning combining Nonlinear Auto-Regressive Neural Networks with …
based on hierarchical learning combining Nonlinear Auto-Regressive Neural Networks with …
An overview and comparative analysis of recurrent neural networks for short term load forecasting
The key component in forecasting demand and consumption of resources in a supply
network is an accurate prediction of real-valued time series. Indeed, both service …
network is an accurate prediction of real-valued time series. Indeed, both service …
Real-time reservoir operation using recurrent neural networks and inflow forecast from a distributed hydrological model
Large-scale reservoirs play an essential role in water resources management for agriculture
irrigation, water supply and flood controls. However, we need robust reservoir operation …
irrigation, water supply and flood controls. However, we need robust reservoir operation …
Long-term time series prediction with the NARX network: An empirical evaluation
The NARX network is a dynamical neural architecture commonly used for input–output
modeling of nonlinear dynamical systems. When applied to time series prediction, the NARX …
modeling of nonlinear dynamical systems. When applied to time series prediction, the NARX …
State of charge estimation for lithium-ion battery using recurrent NARX neural network model based lighting search algorithm
State of charge (SOC) is one of the crucial parameters in a lithium-ion battery. The accurate
estimation of SOC guarantees the safe and efficient operation of a specific application …
estimation of SOC guarantees the safe and efficient operation of a specific application …