Search alternatives:
processing optimization » process optimization (Expand Search), process optimisation (Expand Search), routing optimization (Expand Search)
based optimization » whale optimization (Expand Search)
speech processing » pre processing (Expand Search)
binary 2 » binary _ (Expand Search), binary b (Expand Search)
2 based » _ based (Expand Search), 1 based (Expand Search), ai based (Expand Search)
processing optimization » process optimization (Expand Search), process optimisation (Expand Search), routing optimization (Expand Search)
based optimization » whale optimization (Expand Search)
speech processing » pre processing (Expand Search)
binary 2 » binary _ (Expand Search), binary b (Expand Search)
2 based » _ based (Expand Search), 1 based (Expand Search), ai based (Expand Search)
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61
Initial weight values and correlation thresholds.
Published 2025“…To achieve this, publicly available datasets—Carnegie Mellon University Multimodal Opinion Sentiment Intensity (CMU-MOSI) and Interactive Emotional Dyadic Motion Capture (IEMOCAP)—are employed to collect speech, visual, and textual data relevant to multimodal interaction scenarios. …”
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62
Ablation experiment results comparison.
Published 2025“…To achieve this, publicly available datasets—Carnegie Mellon University Multimodal Opinion Sentiment Intensity (CMU-MOSI) and Interactive Emotional Dyadic Motion Capture (IEMOCAP)—are employed to collect speech, visual, and textual data relevant to multimodal interaction scenarios. …”
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63
Adjustment step size.
Published 2025“…To achieve this, publicly available datasets—Carnegie Mellon University Multimodal Opinion Sentiment Intensity (CMU-MOSI) and Interactive Emotional Dyadic Motion Capture (IEMOCAP)—are employed to collect speech, visual, and textual data relevant to multimodal interaction scenarios. …”
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64
Curve of data size vs. running time.
Published 2025“…To achieve this, publicly available datasets—Carnegie Mellon University Multimodal Opinion Sentiment Intensity (CMU-MOSI) and Interactive Emotional Dyadic Motion Capture (IEMOCAP)—are employed to collect speech, visual, and textual data relevant to multimodal interaction scenarios. …”
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65
Data (3).
Published 2025“…To achieve this, publicly available datasets—Carnegie Mellon University Multimodal Opinion Sentiment Intensity (CMU-MOSI) and Interactive Emotional Dyadic Motion Capture (IEMOCAP)—are employed to collect speech, visual, and textual data relevant to multimodal interaction scenarios. …”
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66
Pseudo Code of RBMO.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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67
P-value on CEC-2017(Dim = 30).
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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68
Memory storage behavior.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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69
Elite search behavior.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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70
Description of the datasets.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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71
S and V shaped transfer functions.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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72
S- and V-Type transfer function diagrams.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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73
Collaborative hunting behavior.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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74
Friedman average rank sum test results.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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75
IRBMO vs. variant comparison adaptation data.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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76
Analysis and design of algorithms for the manufacturing process of integrated circuits
Published 2023“…The (approximate) solution proposals of state-of-the-art methods include rule-based approaches, genetic algorithms, and reinforcement learning. …”
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77
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78
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79
Testing results for classifying AD, MCI and NC.
Published 2024“…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”
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80
Summary of existing CNN models.
Published 2024“…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”