Results 31 to 40 of about 319 (155)

A Hybrid Framework for Stock Price Forecasting Using Metaheuristic Feature Selection Approaches and Transformer Models Enhanced by Temporal Embedding and Attention Pruning

Applied AI Letters, Volume 7, Issue 1, February 2026.
Workflow of the proposed hybrid BWO‐Transformer framework for stock price prediction. ABSTRACT Accurately predicting stock prices remains a major challenge in financial analytics due to the complexity and noise inherent in market data. Feature selection plays a critical role in improving both computational efficiency and predictive performance. In this
Amirhossein Malakouti Semnani, Sohrab Kordrostami, Amirhossein Refahi Sheikhani, Mohammad Hossein Moattar   +3 more
wiley   +1 more source

A Honey Badger Optimization for Minimizing the Pollutant Environmental Emissions-Based Economic Dispatch Model Integrating Combined Heat and Power Units

Energies, 2022
Traditionally, the Economic Dispatch Model (EDM) integrating Combined Heat and Power (CHP) units aims to reduce fuel costs by managing power-only, CHP, and heat-only units.
Ragab El-Sehiemy, Abdullah Shaheen, Ahmed Ginidi, Mostafa Elhosseini   +3 more
doaj   +1 more source

Energy Consumption Prediction Based on PSO–LSTM: A Case Study for a Hospital Heating System

International Journal of Energy Research, Volume 2026, Issue 1, 2026.
Global climate change is closely related to the continuous growth of building energy consumption. Therefore, studying and reducing building energy consumption is of great significance for improving the global energy consumption situation. Hospitals, as high‐energy‐consuming public buildings, require urgent research on energy conservation and reduction.
Yu Liu, Jinliang Wang, Yinan Zhao, Chao Deng, Xing Yuan, Siyuan Tian, Weixiang Gao, Chika Maduabuchi   +7 more
wiley   +1 more source

Year‐Long Robust DG Allocation and Probability‐Based Battery Scheduling in Uncertain Hybrid Renewable Energy System Using GO and BRO Algorithms

International Transactions on Electrical Energy Systems, Volume 2026, Issue 1, 2026.
Escalating load demand at the distribution level necessitates the incorporation of distributed generators (DGs) into power systems. Consequently, the utilization of DGs into power systems based on renewable energy has become a primary approach in the pursuit of affordable and sustainable energy supply.
Asad Abbas, Intisar Ali Sajjad, Jonghoon Kim, Dhanamjayulu C.   +3 more
wiley   +1 more source

High-Accuracy Photovoltaic Power Prediction under Varying Meteorological Conditions: Enhanced and Improved Beluga Whale Optimization Extreme Learning Machine

Energies
Accurate photovoltaic (PV) power prediction plays a crucial role in promoting energy structure transformation and reducing greenhouse gas emissions. This study aims to improve the accuracy of PV power generation prediction. Extreme learning machine (ELM)
Wei Du, Shi-Tao Peng, Pei-Sen Wu, Ming-Lang Tseng   +3 more
doaj   +1 more source

A Multistrategy Improved Archimedes Optimization Algorithm for Solving Engineering Problems

Journal of Mathematics, Volume 2026, Issue 1, 2026.
Given the shortcomings of the Archimedes optimization algorithm (AOA), the traditional AOA exhibits the following limitations: the initialization phase employs a uniform 0‐1 random number distribution to generate sequences, resulting in limited diversity of initial solutions.
Xiaoping Xu, Yajing Cao, Wenbo Li, Yu Zhang, Feng Wang, Yike Li, Pramita Mishra   +6 more
wiley   +1 more source

Modeling landslide susceptibility based on convolutional neural network coupling with metaheuristic optimization algorithms

International Journal of Digital Earth, 2023
Landslides are one of the most common geological hazards worldwide, especially in Sichuan Province (Southwest China). The current study's main purposes are to explore the potential applications of convolutional neural networks (CNN) hybrid ensemble ...
Zhuo Chen, Danqing Song
doaj   +1 more source

FInCH: Fast statistical inference for continuous‐time animal movement

Methods in Ecology and Evolution, Volume 16, Issue 7, Page 1437-1459, July 2025.
Abstract It is common for movement ecologists to model individual‐level animal movement in discrete time using methods such as hidden Markov models (HMMs). Although often the fitting of HMMs is computationally efficient, the key assumptions required to model in discrete time become limiting when dealing with temporally irregular data or an animal that ...
Dominic Grainger, Paul G. Blackwell
wiley   +1 more source

Optimal Control Strategy for Stability Performance Improvement of Hybrid Power Systems With Electric Vehicle Integration

Energy Science &Engineering, Volume 13, Issue 6, Page 2772-2787, June 2025.
ABSTRACT The present article explores the frequency control of hybrid power systems integrated with electric vehicles (EVs). The hybrid power system is a complicated nonlinear entity that highlights the significant issue of dynamic control owing to inadequate damping under fluctuating load conditions.
Zahid Farooq, Shameem Ahmad Lone, Taha Selim Ustun, Asadur Rahman, Ahmet Onen, Cagil Ozansoy   +5 more
wiley   +1 more source

A hybrid optimization approach to evaluating load capacity in distribution networks with new energy and energy storage integration

IET Renewable Power Generation, Volume 19, Issue 1, January/December 2025.
This paper explored the impact of new energy and energy storage integration into distribution network load‐carrying capacity and proposed a method for evaluating the load‐carrying capacity of the distribution networks by improving GA‐BWO with voltage adaptive control.
Longtian Zhang, Delin Wang, Jun Wang, Muhammad Shahid Mastoi, Zelin He, Mannan Hassan   +5 more
wiley   +1 more source