Search alternatives:
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
case optimization » based optimization (Expand Search), phase optimization (Expand Search), dose optimization (Expand Search)
based function » based functional (Expand Search), basis function (Expand Search), basis functions (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
based case » base case (Expand Search), based cancer (Expand Search)
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
case optimization » based optimization (Expand Search), phase optimization (Expand Search), dose optimization (Expand Search)
based function » based functional (Expand Search), basis function (Expand Search), basis functions (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
based case » base case (Expand Search), based cancer (Expand Search)
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MSE for ILSTM algorithm in binary classification.
Published 2023“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”
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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. …”