Showing 1 - 20 results of 78 for search '(( binary more model optimization algorithm ) OR ( total sampling design optimization algorithm ))', query time: 1.19s Refine Results
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    MSE for ILSTM algorithm in binary classification. by Asmaa Ahmed Awad (16726315)

    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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    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

    Published 2025
    “…A major challenge in bioprocess simulation is the lack of physical and chemical property databases for biochemicals. A Python-based algorithm was developed for estimating the nonrandom two-liquid (NRTL) model parameters of aqueous binary systems in a straightforward manner from simplified molecular-input line-entry specification (SMILES) strings of substances in a system. …”
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    Hyperparameters of the LSTM Model. by Ahmed M. Elshewey (21463867)

    Published 2025
    “…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …”
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    Prediction results of individual models. by Ahmed M. Elshewey (21463867)

    Published 2025
    “…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …”
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    The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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    IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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    IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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    The AD-PSO-Guided WOA LSTM framework. by Ahmed M. Elshewey (21463867)

    Published 2025
    “…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …”
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    Data Sheet 1_AutoRA: an innovative algorithm for automatic delineation of reference areas in support of smart soil sampling and digital soil twins.pdf by Hugo Rodrigues (5954366)

    Published 2025
    “…In this study, we introduce the autoRA algorithm, an innovative automated soil sampling design method that utilizes Gower’s Dissimilarity Index to delineate RAs automatically. …”
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    Free vibration analysis and optimal design of adhesively bonded double-strap joints by using artificial neural networks by Qi Guo (133147)

    Published 2021
    “…The effects of the adhesive material properties and joint geometrical parameters on the joint dynamic characteristics were investigated in detail using the trained ANNs. The optimum design problem is defined as a multi-objective optimization problem considering maximizing the first natural frequency and corresponding loss factor while minimizing the total structural weight. …”
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    Optimal contrast analysis with heterogeneous variances and budget concerns by Show-Li Jan (3538697)

    Published 2019
    “…Optimal allocation procedures for the Welch-Satterthwaite tests of standardized and unstandardized contrasts are presented to minimize the total sample size with the designated ratios, to meet a desirable power level for the least cost, and to attain the maximum power performance under a fixed cost. …”