Interdisciplinary & Smart Design
Recent Submissions
-
Ensemble Artificial Bee Colony Algorithm and Q-Learning for Multi-Objective Distributed Heterogeneous Flowshop Scheduling Problems with Sequence-Dependent Setup Time
( Institute of Electrical and Electronics Engineers (IEEE) , 2025 , Article)As the global economy develops and people's awareness of environmental protection increases, the efficient scheduling of production lines in workshops has received more and more attention. However, there is very little ... -
A Virtual Domain-Driven Semi-Supervised Hyperbolic Metric Network With Domain-Class Adversarial Decoupling for Aircraft Engine Intershaft Bearings Fault diagnosis
( Institute of Electrical and Electronics Engineers (IEEE) , 2025 , Article)Aircraft engines operate under more demanding and unique environments, which require the inner components to be able to withstand extreme conditions. Intershaft bearings serve as the critical part of power transmission. ... -
A Defense Mechanism Against LOKI Attacks in Federated Learning for Enhancing Big Data Privacy in Mobile Systems
( Institute of Electrical and Electronics Engineers (IEEE) , 2024 , Conference)With the exponential growth of mobile applications, Android systems have become a significant source of big data which provides both vast opportunities and substantial privacy challenges. This makes it essential to adopt ... -
Ensemble deep learning for Alzheimer’s disease characterization and estimation
( Springer Nature , 2024 , Article)Alzheimer’s disease, which is characterized by a continual deterioration of cognitive abilities in older people, is the most common form of dementia. Neuroimaging data, for example, from magnetic resonance imaging and ... -
Wind Speed Forecasting Using an Ensemble Deep Random Vector Functional Link Neural Network Based on Parsimonious Channel Mixing
( Institute of Electrical and Electronics Engineers (IEEE) , 2024 , Conference)The electricity generation through wind energy is rapidly expanding, primarily due to its priorities of lower carbon emissions and sustainability. Precise wind speed forecasting is essential for renewable energy conversions ... -
A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems
( Institute of Electrical and Electronics Engineers (IEEE) , 2025 , Article)Federated Learning (FL) is gaining traction in Android-based consumer electronics, enabling collaborative model training across decentralized devices while preserving data privacy. However, the increasing adoption of FL ... -
Shipping economic forecasting: recent developments, applications, and future directions
( Taylor and Francis , 2025 , Article)Forecasting is vital in shipping economics and directly affects the business decisions of shipping companies and the quality development of the shipping markets. This study critically reviews variables, methods, and results ... -
Dynamic economic dispatch of multi-area wind-solar-thermal power systems with fractional order comprehensive learning differential evolution
( Elsevier , 2025 , Article)The significance of multi-area dynamic economic dispatch (MADED) is amplified by the integration of wind and solar energy sources which introduces considerable fluctuations. In this work, a MADED model incorporating wind ... -
Economic emission dispatch of power systems considering uncertainty of wind-solar-hydro with fractional order multi-objective differential evolution
( Elsevier , 2025 , Article)The integration of renewable energy brings significant uncertainty to the operation of power systems. Multi-objective economic emission dispatch (MOEED) becomes an important way to reduce operating costs and emissions under ... -
Auxiliary population-assisted differential evolution for multi-area economic dispatch considering valve point effects
( Elsevier , 2025 , Article)Multi-area economic dispatch (MAED) is an indispensable task in the power system's operation. Nevertheless, the valve point effects of generating units make the problem highly nonlinear and non-convex. In this paper, a ... -
A review on metaheuristics for solving home health care routing and scheduling problems
( Elsevier , 2025 , Article)Nowadays, the healthcare of elderly people catches wide attention since the increase of aging population puts significant pressure on public medical resources. The population aging and scarce care resources are likely to ... -
Beyond a single solution: Liquefied natural gas process optimization using niching-enhanced meta-heuristics
( Elsevier , 2025 , Article)The escalating global energy demand and the imperative to mitigate climate change necessitate optimizing the natural gas liquefaction process to enhance energy efficiency, reduce costs, and improve sustainability. Traditional ... -
Drone on-demand delivery routing problem considering order splitting and battery swapping
( Elsevier , 2025 , Article)The use of drone delivery has catalyzed technological innovation within the logistics industry. This delivery mode can reduce on-demand delivery times by up to 50 %, while also significantly lowering labor costs and ... -
Class-incremental Learning for Time Series: Benchmark and Evaluation
( Association for Computing Machinery (ACM) , 2024 , Conference)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 ... -
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 ... -
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 ... -
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 ... -
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 ... -
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 ... -
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 ...
RSS 1.0