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Research Units [5715 items ]
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Student Thesis & Dissertations [1710 items ]
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University Publications [4495 items ]
Recent Submissions
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Energy-efficient multi-objective distributed assembly permutation flowshop scheduling by Q-learning based meta-heuristics
( Elsevier , 2024 , Article)This study addresses energy-efficient multi-objective distributed assembly permutation flowshop scheduling problems with minimisation of maximum completion time, mean of earliness and tardiness, and total carbon emission ... -
An archive-assisted multi-modal multi-objective evolutionary algorithm
( Elsevier , 2024 , Article)The multi-modal multi-objective optimization problems (MMOPs) pertain to characteristic of the decision space that exhibit multiple sets of Pareto optimal solutions that are either identical or similar. The resolution of ... -
A staged fuzzy evolutionary algorithm for constrained large-scale multiobjective optimization
( Elsevier , 2024 , Article)Constrained multiobjective optimization problems (CMOPs) are prevalent in practical applications, where constraints play a significant role. Building on techniques from constrained single-objective optimization, classical ... -
Class-incremental Learning for Time Series: Benchmark and Evaluation
( Association for Computing Machinery (ACM) , 2024 , Conference Proceedings)Real-world environments are inherently non-stationary, frequently introducing new classes over time. This is especially common in time series classification, such as the emergence of new disease classification in healthcare ... -
Constrained large-scale multiobjective optimization based on a competitive and cooperative swarm optimizer
( Elsevier , 2024 , Article)Many engineering application problems can be modeled as constrained multiobjective optimization problems (CMOPs), which have attracted much attention. In solving CMOPs, existing algorithms encounter difficulties in balancing ... -
Vanilla Gradient Descent for Oblique Decision Trees
( IOS Press , 2024 , Conference)Decision Trees (DTs) constitute one of the major highly non-linear AI models, valued, e.g., for their efficiency on tabular data. Learning accurate DTs is, however, complicated, especially for oblique DTs, and does take a ... -
Prediction and Feedback Assisted Evolutionary Algorithms for Scheduling Urban Traffic Signals
( Institute of Electrical and Electronics Engineers Inc. (IEEE) , 2025 , Article)With the acceleration of urbanization, the traffic congestion issue is becoming more and more prominent in large cities. The effective scheduling of urban traffic signals becomes critical. This study proposes three novel ... -
Resilience Framework for Applying Virtual Processes for Accreditation in Higher Education to Address a Disruptive Situation
( Emerald Publishing , 2025 , Dataset)This paper presents a resilience framework for implementing academic accreditation activities in higher education, with a focus on lessons learned from unexpected situations. It explores how the pandemic challenged academic ... -
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
( 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 ... -
A meta-heuristic algorithm combined with deep reinforcement learning for multi-sensor positioning layout problem in complex environment
( Elsevier , 2025 , Article)In a multi-sensor positioning system (MSPS), the layout of sensors plays a crucial role in determining the system’s performance. Therefore, addressing the sensor layout problem (SLP) within the MSPS is an essential approach ... -
Adaptive Hierarchical Graph Cut for Multi-granularity Out-of-distribution Detection
( 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 ... -
Wave energy forecasting: A state-of-the-art survey and a comprehensive evaluation
( 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
( 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 ... -
Complementary Learning Subnetworks towards Parameter-Efficient Class-Incremental Learning
( Institute of Electrical and Electronics Engineers Inc. (IEEE) , 2025 , Article)In the scenario of class-incremental learning (CIL), deep neural networks have to adapt their model parameters to non-stationary data distributions, e.g., the emergence of new classes over time. To mitigate the catastrophic ...
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