Results 41 to 50 of about 369 (162)

Adaptive Acoustic Monitoring for Endangered Cook Inlet Beluga Whales in Complex Soundscapes

Marine Mammal Science, Volume 42, Issue 3, July 2026.
ABSTRACT Effective conservation of the endangered Cook Inlet beluga whale (Delphinapterus leucas) requires comprehensive spatiotemporal data, yet monitoring efforts remain spatially biased, underrepresenting important southern habitats. Passive acoustic monitoring (PAM) provides the necessary broad‐scale coverage, but its expansion introduces ...
Manuel Castellote, Rahul Dodhia, Daniela Ruiz, Zhongqi Miao, Pablo Arbelaez, Verena Gill, Lori Polasek, Juan M. Lavista Ferres   +7 more
wiley   +1 more source

A High‐Accuracy TEC Model for Low‐Mid Latitudes Using a BWO‐Optimized CNN‐xLSTM Hybrid Model With Multi‐Instrument Data Fusion

Space Weather, Volume 24, Issue 4, April 2026.
Abstract The total electron content (TEC) in the ionosphere is strongly affected by solar activity and geomagnetic disturbances in mid‐ and low‐latitude regions, making it a major source of error in GNSS navigation and communication systems. To improve the prediction accuracy of ionospheric TEC, this study proposes a deep learning model—Beluga Whale ...
Wang Li, Jitong Li, Jiale Li, Guanyu Chen, Dongsheng Zhao, Longjiang Li, Xiaoqing Zuo, Kefei Zhang   +7 more
wiley   +1 more source

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

Developing a Quadratic Interpolation Northern Goshawk Optimiser and Its Application for Solving Electrical Engineering Problems

IET Renewable Power Generation, Volume 20, Issue 1, January/December 2026.
We propose an enhanced metaheuristic algorithm, quadratic interpolation northern goshawk optimisation (QINGO), that integrates the generalised quadratic interpolation method into the northern goshawk optimisation framework. The proposed algorithm shows superior convergence, stability, and accuracy compared with several existing methods on standard ...
Ahmed H. A. Adam, Salah Kamel, Mohamed H. Hassan   +2 more
wiley   +1 more source

Short‐ and Long‐Term Load Forecasting Using VMD With Temporal Dual Learners Network: A Case Study in Kuwait

International Journal of Energy Research, Volume 2026, Issue 1, 2026.
Forecasting the demand for electrical load precisely is essential for the steady and energy‐efficient operation of today’s power systems, especially in places where there is much variability in demand. In this study, we propose a novel hybrid deep learning framework, termed variational mode decomposition with temporal dual learners network (VMD‐TDLNet),
Maha Alqallaf, Nour Hameed Hasan, Dina Alostath, Salman Zakareya, Özgür Ömer Ersin   +4 more
wiley   +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

Distributed Hybrid Flowline Rescheduling Based on Improved Gray Wolf Optimization Algorithm [PDF]

Zhengzhou Daxue xuebao. Gongxue ban
Distributed hybrid flowline rescheduling was investigated considering machine breakdown and transportation time constraints. An integer programming model was constructed with the optimization objective of simultaneously minimizing the maximum ...
XUAN Hua, XIONG Mengying, CAO Ying
doaj   +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

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