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Optimizing COVID-19 control measures using multi-objective deep reinforcement learning
Published 2024“…The study highlights the potential of multi-objective deep reinforcement learning as a method of optimizing public health interventions by shedding light on the optimum COVID-19 control methods for various scenarios and models. …”
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Optimal design of a guided wave rail web transducor using numerical modelling
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An evaluation of inertial motion capture technology for use in the analysis and optimization of road cycling kinematics
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A spin on compressive sensing imaging : reticle-based single-pixel imaging system
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The use of reflectance classification for chlorophyll algorithm application across multiple optical water types in South African coastal waters
Published 2017“…The blended Chl α product consists of weighted retrievals from five different algorithms, including two 4th order polynomial exponential algorithms utilizing the blue-green spectral region, two red-NIR band ratio algorithms, and a neural network. …”
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Development of a non-invasive water flow meter for a smart geyser
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A Market approach to balance services pricing
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Resource management in IP networks
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Induction of fuzzy rules from chemical process data using Growing Neural Gas and Reactive Tabu search methods
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The Simultaneous Optimization of the Nose and Tail Geometry of a High-Speed Train for Drag and Crosswind Stability
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Bayesian optimal filtering in dynamic linear models: an empirical study of economic time series data
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A study of gradient based particle swarm optimisers
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Simulation-based Optimized Production Policy for Hybrid MTS/MTO Glass Tube Manufacturing Systems
Published 2018“…Based on the simulation model, an optimization algorithm is applied to select optimum parameters for proposed policy with the objective of minimizing total costs. …”
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Motion planning for a rotary-wing UAV in dynamic environments
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A Bayesian extreme value approach to the optimal reinsurance problem in a multivariate risk setting
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Modeling and optimization of single-leg multi-fare class overbooking problem: the case of Ethiopian Airlines
Published 2012“…The overbooking model developed was solved using both a closed form approach using derivatives and Monte Carlo simulation with a derivative free optimization algorithm. A comparison of the revenue generated from no-overbooking policy, the closed form solution, and the Monte Carlo simulation solution approach shows that the Monte Carlo simulation solution approach performs well. …”
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