Results 161 to 170 of about 90,690 (297)

Πρόβλεψη τροχιάς αεροσκάφους με την χρήση νευρωνικών δικτύων LSTM

, 2018
Ζαχόπουλος, Γιώργος
openalex   +1 more source

Research on Collaborative Estimation of SOC and SOH for Lithium‐Ion Batteries Based on BS‐SRCKF‐DEKF

Energy Science &Engineering, EarlyView.
This paper presents a novel method for jointly estimating the state of charge (SOC) and state of health (SOH) in lithium‐ion battery systems. A second‐order hysteresis RC model and the BS‐SRCKF‐DEKF algorithm are used to improve estimation accuracy. Simulation and experimental results verify the method′s robustness and superior performance.
Meijin Lin, Haokun Lin, Jiehua Tan
wiley   +1 more source

A novel hybrid model for emotion detection in text through sequential and transformer-based approaches: LSTM enhanced RoBERTa (LER). [PDF]

Sci Rep
Khan B, Usman M, Binsawad M.
europepmc   +1 more source

Tomtit‐Raven Evolutionary Selector‐Reinforced Attention‐Driven: A High‐Performance and Computationally Efficient Cyber Threat Detection Framework for Smart Grids

Energy Science &Engineering, EarlyView.
Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga, Praveen Kumar Balachandran, Umawathy Techanamurthy, Muhammad Ammirrul Atiqi Mohd Zainuri   +3 more
wiley   +1 more source

Chiller sensor fault diagnosis based on circle mapping and adaptive t-distribution Runge-Kutta algorithm optimized LSTM. [PDF]

Sci Rep
Wang Y, Liu J, Liu F, Duan X.
europepmc   +1 more source

Predicting Parameters Affecting Building Energy Consumption Using Machine Learning Models

Energy Science &Engineering, EarlyView.
This framework integrates long‐term weather forecasting with building energy simulation to predict energy demand. The CNN–LSTM model achieved the highest accuracy (R2 ≈ 0.95), supporting smart HVAC control with ~ 15% energy savings. ABSTRACT The rapid growth of population and the construction industry have led to an increase in energy demand and an ...
Bassam Musheer Kareem, Abdolsalam Ebrahimpour, Jafar Ghafouri, Roghayyeh Motallebzadeh   +3 more
wiley   +1 more source

Attention-Enhanced CNN-LSTM with Spatial Downscaling for Day-Ahead Photovoltaic Power Forecasting. [PDF]

Sensors (Basel)
Peng F, Tang X, Xiao M.
europepmc   +1 more source

Investigating the performance of DistilBert and LSTM-CNN models with GloVe embeddings for emotion detection from textual data

Wenhong Zhao, Wei Wang
openalex   +1 more source

Machine Learning and Artificial Intelligence Techniques for Intelligent Control and Forecasting in Energy Storage‐Based Power Systems

Energy Science &Engineering, EarlyView.
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan, Suresh Panchanathan, Chan Choon Kit, Elumalai Perumal Venkatesan, Nasim Hasan   +4 more
wiley   +1 more source

Low-SNR and BER reduction in UWOC systems using DESN and CNN-TCN deep learning models. [PDF]

Sci Rep
Salama WM, Aly MH, Amer ES.
europepmc   +1 more source