Unit equipment parameters. حسب Kuiyuan Pan (21145338)

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Numerical results under different algorithms. حسب Kuiyuan Pan (21145338)

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Weight coefficients change curve. حسب Kuiyuan Pan (21145338)

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Wind power forecast curve. حسب Kuiyuan Pan (21145338)

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Value evaluation system. حسب Kuiyuan Pan (21145338)

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Box plots of different algorithms. حسب Kuiyuan Pan (21145338)

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Benchmark function. حسب Kuiyuan Pan (21145338)

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Comparison of processing time for various models. حسب Nan Zhang (46264)

"…Therefore, a palm print recognition model that integrates regions of interest and Gabor filters has been proposed to solve the problem of difficulty in feature extraction caused by factors such as noise, lighting changes, and acquisition angles that often affect palm print images during the acquisition process. …"

Analysis of processing time for each model. حسب Nan Zhang (46264)

"…Therefore, a palm print recognition model that integrates regions of interest and Gabor filters has been proposed to solve the problem of difficulty in feature extraction caused by factors such as noise, lighting changes, and acquisition angles that often affect palm print images during the acquisition process. …"

Confusion Matrix of LSTM. حسب Chao Zeng (452370)

"…The main challenges include deficiency of data acquisition, signal features extracting complex process, and insufficient robustness of models. To enhance the precision of forecasting consequence, a circular saw blade wear prediction method combining generative adversarial network (GAN) and CNN-LSTM models is proposed. …"

Convolutional Neural Network. حسب Chao Zeng (452370)

"…The main challenges include deficiency of data acquisition, signal features extracting complex process, and insufficient robustness of models. To enhance the precision of forecasting consequence, a circular saw blade wear prediction method combining generative adversarial network (GAN) and CNN-LSTM models is proposed. …"

LSTM Network Structure. حسب Chao Zeng (452370)

"…The main challenges include deficiency of data acquisition, signal features extracting complex process, and insufficient robustness of models. To enhance the precision of forecasting consequence, a circular saw blade wear prediction method combining generative adversarial network (GAN) and CNN-LSTM models is proposed. …"

Generative Adversarial Network. حسب Chao Zeng (452370)

"…The main challenges include deficiency of data acquisition, signal features extracting complex process, and insufficient robustness of models. To enhance the precision of forecasting consequence, a circular saw blade wear prediction method combining generative adversarial network (GAN) and CNN-LSTM models is proposed. …"

Sawtooth mesh distortion. حسب Chao Zeng (452370)

"…The main challenges include deficiency of data acquisition, signal features extracting complex process, and insufficient robustness of models. To enhance the precision of forecasting consequence, a circular saw blade wear prediction method combining generative adversarial network (GAN) and CNN-LSTM models is proposed. …"

Performance Comparison of Models. حسب Chao Zeng (452370)

"…The main challenges include deficiency of data acquisition, signal features extracting complex process, and insufficient robustness of models. To enhance the precision of forecasting consequence, a circular saw blade wear prediction method combining generative adversarial network (GAN) and CNN-LSTM models is proposed. …"

Confusion Matrix of RBFNN. حسب Chao Zeng (452370)

"…The main challenges include deficiency of data acquisition, signal features extracting complex process, and insufficient robustness of models. To enhance the precision of forecasting consequence, a circular saw blade wear prediction method combining generative adversarial network (GAN) and CNN-LSTM models is proposed. …"

PCC-optimized GAN model. حسب Chao Zeng (452370)

"…The main challenges include deficiency of data acquisition, signal features extracting complex process, and insufficient robustness of models. To enhance the precision of forecasting consequence, a circular saw blade wear prediction method combining generative adversarial network (GAN) and CNN-LSTM models is proposed. …"

J-C damage model parameters. حسب Chao Zeng (452370)

"…The main challenges include deficiency of data acquisition, signal features extracting complex process, and insufficient robustness of models. To enhance the precision of forecasting consequence, a circular saw blade wear prediction method combining generative adversarial network (GAN) and CNN-LSTM models is proposed. …"

Measurement of saw blade wear value. حسب Chao Zeng (452370)

"…The main challenges include deficiency of data acquisition, signal features extracting complex process, and insufficient robustness of models. To enhance the precision of forecasting consequence, a circular saw blade wear prediction method combining generative adversarial network (GAN) and CNN-LSTM models is proposed. …"

Basic structure model of saw blade. حسب Chao Zeng (452370)

"…The main challenges include deficiency of data acquisition, signal features extracting complex process, and insufficient robustness of models. To enhance the precision of forecasting consequence, a circular saw blade wear prediction method combining generative adversarial network (GAN) and CNN-LSTM models is proposed. …"