Ltpnet integration of deep learning and environmental decision support systems for renewable energy demand forecasting

T Li, M Zhang, Y Zhou - arXiv preprint arXiv:2410.15286, 2024 - arxiv.org
Against the backdrop of increasingly severe global environmental changes, accurately
predicting and meeting renewable energy demands has become a key challenge for …

Complex-valued artificial hummingbird algorithm for global optimization and short-term wind speed prediction

L Feng, Y Zhou, Q Luo, Y Wei - Expert Systems with Applications, 2024 - Elsevier
Environmental pollution and energy depletion have spurred the exploration of renewable
energy sources. Wind energy, with its sustainability and eco-friendliness, stands out as a …

On the Cryptanalysis of a Simplified AES Using a Hybrid Binary Grey Wolf Optimization

RM Rizk-Allah, H Abdulkader, SSA Elatif, D Oliva… - Mathematics, 2023 - mdpi.com
Cryptosystem cryptanalysis is regarded as an NP-Hard task in modern cryptography. Due to
block ciphers that are part of a modern cipher and have nonlinearity and low autocorrelation …

Combination of Metaheuristic Algorithm and Artificial Neural Networks Model to Forecast Wind Energy

D Bouabdallaoui, T Haidi, EM Mellouli… - … Research in Applied …, 2024 - ieeexplore.ieee.org
The transition to renewable energies, in particular wind power, is essential to meeting
environmental challenges and ensuring a sustainable future. Precise estimation of wind …

Investigating Neural Network-Based Deep Learning Strategies for Real-Time Data Analysis in Machine Learning

S Walke, M Nalluri, R Lavanya… - … on Power Energy …, 2023 - ieeexplore.ieee.org
there are numerous distinct strategies and techniques that fall under the huge class of
neural network-primarily based deep gaining knowledge of in device getting to know. those …