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function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
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function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation 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)
based swarm » based sars (Expand Search), based smart (Expand Search), based arm (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
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Parameter setting for LSTM.
Published 2023“…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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LITNET-2020 data splitting approach.
Published 2023“…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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Transformation of symbolic features in NSL-KDD.
Published 2023“…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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25
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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26
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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27
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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28
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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29
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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30
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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33
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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Decoding evidence for feature triplets on test tasks.
Published 2025“…<p>Another neural hypothesis formulated based on the SF&GPI algorithm is that feature triplets associated with the optimal training policies should be reactivated on test trials. …”
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38
Codes for high-order analytical continuation algorithms based on direct derivation and recursion methods
Published 2024“…The optimal order of the analytical continuation algorithm is contingent upon the noise level of gravity data. …”
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Performance comparison of four optimization methods.
Published 2025“…(B) Relative error convergence of four optimization methods, plotted as a function of the logarithm of iterations. …”
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SBH17: Benchmark Database of Barrier Heights for Dissociative Chemisorption on Transition Metal Surfaces
Published 2022“…The medium algorithm does require metal lattice constants and interlayer distances that are optimized separately for each functional. …”