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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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The bus sightseeing problem
Published 2023“…A mixed-integer programming formulation for the BSP is provided and solved by a Benders decomposition algorithm. For large-scale instances, an iterated local search based metaheuristic algorithm is developed with some tailored neighborhood operators. …”
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Multidimensional Gains for Stochastic Approximation
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An optimal stochastic multivariable PID controller
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Learn while Tracking
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Heuristics for graph decomposition
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A MIMO Sampling-Rate-Dependent Controller
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CFD Based Airfoil Shape Optimization for Aerodynamic Drag Reduction
Published 2012Get full text
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Optimality of first-order ILC among higher order ILC
Published 2006Get full text
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Multigrid solvers in reconfigurable hardware
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Random vector functional link network: Recent developments, applications, and future directions
Published 2023“…Finally, we present potential future research directions/opportunities that can inspire the researchers to improve the RVFL’s architecture and learning algorithm further. …”
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Dynamic Cyber Resilience of Interdependent Critical Information Infrastructures
Published 2021“…The technology stack was also enhanced with three new algorithms and five protocols. The proposed solution was optimized using the iterative four-objective cycle based on previous primary phase results. …”
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Scatter search for homology modeling
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What are artificial intelligence literacy and competency? A comprehensive framework to support them
Published 2024“…We also identify five effective learning experiences to foster abilities and confidences, and suggest five future research directions: prompt engineering, data literacy, algorithmic literacy, self-reflective mindset, and empirical research.…”
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Shuffled Linear Regression with Erroneous Observations
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