بدائل البحث:
feature optimization » resource optimization (توسيع البحث), feature elimination (توسيع البحث), structure optimization (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
task feature » based feature (توسيع البحث), each feature (توسيع البحث), a feature (توسيع البحث)
binary task » binary mask (توسيع البحث)
binary case » binary mask (توسيع البحث), binary image (توسيع البحث), primary case (توسيع البحث)
case design » based design (توسيع البحث), game design (توسيع البحث), core design (توسيع البحث)
feature optimization » resource optimization (توسيع البحث), feature elimination (توسيع البحث), structure optimization (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
task feature » based feature (توسيع البحث), each feature (توسيع البحث), a feature (توسيع البحث)
binary task » binary mask (توسيع البحث)
binary case » binary mask (توسيع البحث), binary image (توسيع البحث), primary case (توسيع البحث)
case design » based design (توسيع البحث), game design (توسيع البحث), core design (توسيع البحث)
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41
Transformation of symbolic features in NSL-KDD.
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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42
Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP
منشور في 2022"…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …"
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43
Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
منشور في 2020"…In this way, for each binary problem, the CSP algorithm produces features to determine if the specific body part is engaged in the task or not. …"
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44
Models and Dataset
منشور في 2025"…The algorithm does not rely on predefined control parameters like crossover or mutation rates, which makes it lightweight and easy to implement for various feature selection and optimization tasks.…"