بدائل البحث:
group classification » risk classification (توسيع البحث), improve classification (توسيع البحث), perform classification (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data group » ta group (توسيع البحث)
binary 1 » binary _ (توسيع البحث)
1 based » _ based (توسيع البحث)
group classification » risk classification (توسيع البحث), improve classification (توسيع البحث), perform classification (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data group » ta group (توسيع البحث)
binary 1 » binary _ (توسيع البحث)
1 based » _ based (توسيع البحث)
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MSE for ILSTM algorithm in binary classification.
منشور في 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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Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans.
منشور في 2023"…D, Corresponding performance parameters. All data correspond to binary classification between control and disease cases. …"
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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
منشور في 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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Algorithm for generating hyperparameter.
منشور في 2024"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm
منشور في 2020"…Obtaining a reliable QSAR model with few descriptors is an essential procedure in chemometrics. The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …"
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Results of machine learning algorithm.
منشور في 2024"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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ROC comparison of machine learning algorithm.
منشور في 2024"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
منشور في 2020"…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …"
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Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things
منشور في 2025"…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …"