بدائل البحث:
share optimization » swarm optimization (توسيع البحث), whale optimization (توسيع البحث), phase optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data share » data store (توسيع البحث), data space (توسيع البحث), data sharing (توسيع البحث)
binary 2 » binary _ (توسيع البحث), binary b (توسيع البحث)
2 based » _ based (توسيع البحث), 1 based (توسيع البحث), ai based (توسيع البحث)
share optimization » swarm optimization (توسيع البحث), whale optimization (توسيع البحث), phase optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data share » data store (توسيع البحث), data space (توسيع البحث), data sharing (توسيع البحث)
binary 2 » binary _ (توسيع البحث), binary b (توسيع البحث)
2 based » _ based (توسيع البحث), 1 based (توسيع البحث), ai based (توسيع البحث)
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81
Parameter setting for CBOA and PSO.
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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82
NSL-KDD dataset description.
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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83
The architecture of LSTM cell.
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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84
The architecture of ILSTM.
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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85
Parameter setting for LSTM.
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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86
LITNET-2020 data splitting approach.
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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87
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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88
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89
Parameter settings.
منشور في 2024"…<div><p>Differential Evolution (DE) is widely recognized as a highly effective evolutionary algorithm for global optimization. It has proven its efficacy in tackling diverse problems across various fields and real-world applications. …"
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90
Presentation_1_Modified GAN Augmentation Algorithms for the MRI-Classification of Myocardial Scar Tissue in Ischemic Cardiomyopathy.PPTX
منشور في 2021"…Currently, there are no optimized deep-learning algorithms for the automated classification of scarred vs. normal myocardium. …"
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91
Data_Sheet_1_Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer.pdf
منشور في 2019"…The Digital Annealer's algorithm is currently based on simulated annealing; however, it differs from it in its utilization of an efficient parallel-trial scheme and a dynamic escape mechanism. …"
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92
Quadratic polynomial in 2D image plane.
منشور في 2024"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
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93
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94
Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish)
منشور في 2024"…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …"
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95
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96
Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
منشور في 2020"…Here, we propose a solution to address the limitation of identifiable motor activities by using combined MIs (i.e., MIs involving 2 or more body parts at the same time). 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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97
GSE96058 information.
منشور في 2024"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"
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98
The performance of classifiers.
منشور في 2024"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"
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99
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100
Bayesian sequential design for sensitivity experiments with hybrid responses
منشور في 2023"…To deal with the problem of complex computation involved in searching for optimal designs, fast algorithms are presented using two strategies to approximate the optimal criterion, denoted as SI-optimal design and Bayesian D-optimal design, respectively. …"