Search alternatives:
weight optimization » joint optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
data sampling » water sampling (Expand Search), data samples (Expand Search), data sample (Expand Search)
binary model » final model (Expand Search), injury model (Expand Search), tiny model (Expand Search)
model weight » model weights (Expand Search), body weight (Expand Search), model which (Expand Search)
weight optimization » joint optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
data sampling » water sampling (Expand Search), data samples (Expand Search), data sample (Expand Search)
binary model » final model (Expand Search), injury model (Expand Search), tiny model (Expand Search)
model weight » model weights (Expand Search), body weight (Expand Search), model which (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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DE algorithm flow.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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Test results of different algorithms.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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AUW-CE Mining Algorithms & Dataset Hub
Published 2025“…Moreover, in response to the limitations of conventional cross-entropy methods for HUCPM, four core optimization strategies are designed: optimization of the initial probability distribution to guide the search direction, enhancement of sample diversity to prevent local convergence, dynamic adjustment of sample size to reduce redundant calculations, and incorporation of utility weights to improve the accuracy of probability updates. …”
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