Search alternatives:
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
based function » based functional (Expand Search), basis function (Expand Search), basis functions (Expand Search)
binary mask » binary image (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
based function » based functional (Expand Search), basis function (Expand Search), basis functions (Expand Search)
binary mask » binary image (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
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Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement
Published 2019“…<div><p>Algorithmic differentiation (AD) is an alternative to finite differences (FD) for evaluating function derivatives. …”
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Algorithm of the PbGA search for the optimal PbF.
Published 2024“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”
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Multiobjective Tuning and Performance Assessment of PID Using Teaching–Learning-Based Optimization
Published 2021“…The numerical examples of CPA problems show that the algorithm can generate better MOV than existing methods with less calculation time. …”
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Loss function curve.
Published 2024“…Finally, the loss function CIoU of YOLOv7 is optimized to EIoU loss function to accelerate the convergence speed of the model. …”
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S1 Dataset -
Published 2024“…A novel method for optimizing small-world property is then proposed based on the multiobjective evolutionary algorithm with decomposition. …”
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Statistical tests of ACC on the random network.
Published 2024“…A novel method for optimizing small-world property is then proposed based on the multiobjective evolutionary algorithm with decomposition. …”
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Parameters in the experiment.
Published 2024“…A novel method for optimizing small-world property is then proposed based on the multiobjective evolutionary algorithm with decomposition. …”
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Statistical tests of APL on the random network.
Published 2024“…A novel method for optimizing small-world property is then proposed based on the multiobjective evolutionary algorithm with decomposition. …”
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Statistical tests of ACC on the regular network.
Published 2024“…A novel method for optimizing small-world property is then proposed based on the multiobjective evolutionary algorithm with decomposition. …”
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Statistical tests of APL on the regular network.
Published 2024“…A novel method for optimizing small-world property is then proposed based on the multiobjective evolutionary algorithm with decomposition. …”
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Optimal configuration of RC frames considering ultimate and serviceability limit state constraints
Published 2021“…Structural analyses are performed by using the MASTAN2 software, taking into account geometric nonlinearities and a simplified physical nonlinearity method. The objective function considers the cost of concrete, reinforcement and formwork, and the optimization problems are solved by genetic algorithms. …”
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Genetic algorithm meta-parameters.
Published 2024“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”
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The entity relationship of DDPG algorithm.
Published 2024“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”
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