Short-term multi-hour ahead country-wide wind power prediction for Germany using gated recurrent unit deep learning

S Farah, N Humaira, Z Aneela, E Steffen - Renewable and Sustainable …, 2022 - Elsevier
In recent years, wind power has emerged as an important source of renewable energy.
When onshore and offshore wind farm regions are connected to the grid for power …

[HTML][HTML] Overcoming nonlinear dynamics in diabetic retinopathy classification: a robust AI-based model with chaotic swarm intelligence optimization and recurrent long …

YB Özçelik, A Altan - Fractal and Fractional, 2023 - mdpi.com
Diabetic retinopathy (DR), which is seen in approximately one-third of diabetes patients
worldwide, leads to irreversible vision loss and even blindness if not diagnosed and treated …

Advances in Henry gas solubility optimization: A physics-inspired metaheuristic algorithm with its variants and applications

MA El-Shorbagy, A Bouaouda, HA Nabwey… - IEEE …, 2024 - ieeexplore.ieee.org
The Henry Gas Solubility Optimization (HGSO) is a physics-based metaheuristic inspired by
Henry's law, which describes the solubility of the gas in a liquid under specific pressure …

Distributed tri-layer risk-averse stochastic game approach for energy trading among multi-energy microgrids

Z Li, L Wu, Y Xu, L Wang, N Yang - Applied Energy, 2023 - Elsevier
This paper discusses a tri-layer non-cooperative energy trading approach among multiple
grid-tied multi-energy microgrids (MEMGs) in the restructured integrated energy market. The …

[HTML][HTML] High-pressure supersonic carbon dioxide (CO2) separation benefiting carbon capture, utilisation and storage (CCUS) technology

H Ding, Y Zhang, Y Dong, C Wen, Y Yang - Applied Energy, 2023 - Elsevier
Carbon capture, utilisation and storage (CCUS) is of unique significance for building a green
and resilient energy system, and it is also a key solution to tackle the climate challenge. The …

DAFA-BiLSTM: Deep autoregression feature augmented bidirectional LSTM network for time series prediction

H Wang, Y Zhang, J Liang, L Liu - Neural Networks, 2023 - Elsevier
Time series forecasting models that use the past information of exogenous or endogenous
sequences to forecast future series play an important role in the real world because most …

A novel lithium-ion battery state of charge estimation method based on the fusion of neural network and equivalent circuit models

A Tang, Y Huang, S Liu, Q Yu, W Shen, R **ong - Applied Energy, 2023 - Elsevier
Accurate estimating the state of charge (SOC) can improve battery reliability, safety, and
extend battery service life. The existing battery models used for SOC estimation …

Energy balance via memristor synapse in Morris-Lecar two-neuron network with FPGA implementation

X Yu, H Bao, M Chen, B Bao - Chaos, Solitons & Fractals, 2023 - Elsevier
Synapses can regulate the energy balance in the neural network. In this work, a two-neuron
network is established by coupling two Morris-Lecar neurons using a memristor synapse …

Multi-objective optimization for impeller structure parameters of fuel cell air compressor using linear-based boosting model and reference vector guided evolutionary …

J Fu, H Wang, X Sun, H Bao, X Wang, J Liu - Applied Energy, 2024 - Elsevier
As a pivotal part of cathode air supply system, centrifugal air compressors play a central
position in ensuring efficient operations of onboard fuel cells. To improve the overall …

How can China achieve the 2030 carbon peak goal—a crossover analysis based on low-carbon economics and deep learning

C Shi, J Zhi, X Yao, H Zhang, Y Yu, Q Zeng, L Li… - Energy, 2023 - Elsevier
This paper studied the carbon peak through the cross-analysis of low-carbon economics
and deep learning. The STIRPAT model and ridge regression was used to distinguish and …