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Wave energy forecasting: A state-of-the-art survey and a comprehensive evaluation
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Elsevier
, 2025 , Article)
Wave energy, a promising renewable energy source, has the potential to diversify the global energy mix significantly. Accurate forecasting of significant wave height (SWH) is crucial for enhancing the efficiency and ...
Underwater Acoustic Signal Denoising Algorithms: A Survey of the State of the Art
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Institute of Electrical and Electronics Engineers Inc. (IEEE)
, 2025 , Article)
Underwater acoustic signal (UAS) denoising is crucial for enhancing the reliability of underwater communication and monitoring systems by mitigating the effects of noise and improving signal clarity. The complex and dynamic ...
A single-objective Sequential Search Assistance-based Multi-Objective Algorithm Framework
(
Elsevier
, 2025 , Article)
In recent years, multi-objective optimization has garnered significant attention from researchers. Evolutionary algorithms are proven to be highly effective in solving complex optimization problems in plenty of cases. ...
An individual adaptive evolution and regional collaboration based evolutionary algorithm for large-scale constrained multiobjective optimization problems
(
Elsevier
, 2025 , Article)
Large-scale constrained multiobjective optimization problems (LSCMOPs) refer to constrained multiobjective optimization problems (CMOPs) with large-scale decision variables. When using evolutionary algorithms to solve ...
High frequency volatility forecasting and risk assessment using neural networks-based heteroscedasticity model
(
Elsevier
, 2025 , Article)
High frequency volatility forecasting is essential for timely risk management and informed decision-making in dynamic financial markets. However, accurate forecasting is challenging due to the rapid nature of market movements ...
Your data is not perfect: Towards cross-domain out-of-distribution detection in class-imbalanced data
(
Elsevier
, 2024 , Article)
Out-of-distribution detection (OOD detection) aims to detect test samples drawn from a distribution that is different from the training distribution, in order to prevent models trained on in-distribution (ID) data from ...
A Reinforced Neighborhood Search Method Combined With Genetic Algorithm for Multi-Objective Multi-Robot Transportation System
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Institute of Electrical and Electronics Engineers Inc. (IEEE)
, 2025 , Article)
With the rapid advancement of artificial intelligence, autonomous multi-robot systems have been successfully applied to various domains. Therefore, developing intelligent routing and scheduling systems to efficiently ...
Alzheimer’s disease diagnosis from MRI and SWI fused image using self adaptive differential evolutionary RVFL classifier
(
Elsevier
, 2025 , Article)
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that involves gradual memory loss and eventually leads to severe cognitive decline at the final stage. Advanced neuroimaging modalities, including magnetic ...
Adaptive Hierarchical Graph Cut for Multi-granularity Out-of-distribution Detection
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Institute of Electrical and Electronics Engineers Inc. (IEEE)
, 2025 , Article)
This paper focuses on a significant yet challenging task: out-of-distribution detection (OOD detection), which aims to distinguish and reject test samples with semantic shifts, so as to prevent models trained on in-distribution ...
Differential evolution-based mixture distribution models for wind energy potential assessment: A comparative study for coastal regions of China
(
Elsevier
, 2025 , Article)
Mixture distributions generally have higher flexibility than single distributions in describing wind speeds. However, the determination of their components is critical. This work evaluates suitable distributions for the ...