DNN structure consisting of many hidden layers. by Cihun-Siyong Alex Gong (11874066)

Modern LSTM units and its layer structure are illustrated. by Cihun-Siyong Alex Gong (11874066)

Judgment matrix of control layer U. by Yixuan Lu (9987980)

CNN structure. by Guangmei Ma (21432861)

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Judgment matrix of criterion layer U₃. by Yixuan Lu (9987980)

Judgment matrix of criterion layer U₄. by Yixuan Lu (9987980)

Judgment matrix of criterion layer U₂. by Yixuan Lu (9987980)

Judgment matrix of criterion layer U₁. by Yixuan Lu (9987980)

Multi-scale representation of two-dimensional linear graphs. by Guangmei Ma (21432861)

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Expert scoring values of criterion layer U₁. by Yixuan Lu (9987980)

Comparison of optimization results. by Lijie Sun (224007)

“…The process employs Maximum Second-order Cyclostationary Blind Deconvolution (CYCBD) to filter out noise from the vibration signals emitted by bearings; secondly, considering the issue with the conventional Harris Hawks Optimization (HHO) algorithm which tends to prematurely converge to local optima, the differential evolution mutation operator is introduced and the escape energy factor is improved from linear to nonlinear in IHHO; then, a double-layer network model based on DBN-ELM is proposed, to avoid the number of hidden layer nodes of DBN from human experience interference, and IHHO is used to optimize DBN structure, which is denoted as IHHO-DBN-ELM method; with the optimal structure is obtained by using a combined IHHO optimized DBN and ELM; in conclusion, the proposed IHHO-DBN-ELM approach is applied to the bearing fault detection using the Western Reserve University’s bearing fault dataset. …”

The structure of RBM. by Lijie Sun (224007)

“…The process employs Maximum Second-order Cyclostationary Blind Deconvolution (CYCBD) to filter out noise from the vibration signals emitted by bearings; secondly, considering the issue with the conventional Harris Hawks Optimization (HHO) algorithm which tends to prematurely converge to local optima, the differential evolution mutation operator is introduced and the escape energy factor is improved from linear to nonlinear in IHHO; then, a double-layer network model based on DBN-ELM is proposed, to avoid the number of hidden layer nodes of DBN from human experience interference, and IHHO is used to optimize DBN structure, which is denoted as IHHO-DBN-ELM method; with the optimal structure is obtained by using a combined IHHO optimized DBN and ELM; in conclusion, the proposed IHHO-DBN-ELM approach is applied to the bearing fault detection using the Western Reserve University’s bearing fault dataset. …”

The network structure of DBN-ELM. by Lijie Sun (224007)

“…The process employs Maximum Second-order Cyclostationary Blind Deconvolution (CYCBD) to filter out noise from the vibration signals emitted by bearings; secondly, considering the issue with the conventional Harris Hawks Optimization (HHO) algorithm which tends to prematurely converge to local optima, the differential evolution mutation operator is introduced and the escape energy factor is improved from linear to nonlinear in IHHO; then, a double-layer network model based on DBN-ELM is proposed, to avoid the number of hidden layer nodes of DBN from human experience interference, and IHHO is used to optimize DBN structure, which is denoted as IHHO-DBN-ELM method; with the optimal structure is obtained by using a combined IHHO optimized DBN and ELM; in conclusion, the proposed IHHO-DBN-ELM approach is applied to the bearing fault detection using the Western Reserve University’s bearing fault dataset. …”

The experimental basic environmental parameters. by Guangmei Ma (21432861)

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Improved HMAX model running process. by Guangmei Ma (21432861)

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Significant region segmentation. by Guangmei Ma (21432861)

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Comprehensive comparison of existing methods. by Guangmei Ma (21432861)

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Method training loss testing. by Guangmei Ma (21432861)

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Analysis of rotational non-deformation characterization. by Guangmei Ma (21432861)

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Segmentation results of physical images. by Guangmei Ma (21432861)

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