Relationship between strike shift angle, boundary angle, and mining depth/loose layer thickness. by Liangliang Yang (3814120)

Relationship between uphill movement angle, boundary angle, and mining depth/thickness of the loose layer. by Liangliang Yang (3814120)

Comparison of algorithm search curves. by Bowen Li (200859)

“…The optimal parameters such as the width and weight of RBF are determined, and the optimal RDC-RBF fault diagnosis model is established. …”

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

“…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”

DACS optimized RBF flow chart. by Bowen Li (200859)

“…The optimal parameters such as the width and weight of RBF are determined, and the optimal RDC-RBF fault diagnosis model is established. …”

Training configurations of the utilized datasets. by Zhuolin Yang (14658411)

“…Second, a category perception module is used to learn category feature representations and guide the pixel classification process through an attention mechanism to optimize the resulting segmentation accuracy. Finally, an edge optimization module is used to integrate the edge features into the middle and the deep supervision layers of the network through an adaptive algorithm to enhance its ability to express edge features and optimize the edge segmentation effect. …”

Code and raw data used in this study. by Zhuolin Yang (14658411)

“…Second, a category perception module is used to learn category feature representations and guide the pixel classification process through an attention mechanism to optimize the resulting segmentation accuracy. Finally, an edge optimization module is used to integrate the edge features into the middle and the deep supervision layers of the network through an adaptive algorithm to enhance its ability to express edge features and optimize the edge segmentation effect. …”

datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf by Jan Tönshoff (10192709)

Relationship of coal pillar retention parameters. by Liangliang Yang (3814120)

Pumping machine fault diagnosis results table. by Bowen Li (200859)

“…The optimal parameters such as the width and weight of RBF are determined, and the optimal RDC-RBF fault diagnosis model is established. …”

Flowchart of RDC-RBF. by Bowen Li (200859)

“…The optimal parameters such as the width and weight of RBF are determined, and the optimal RDC-RBF fault diagnosis model is established. …”

Confusion matrix of classification results. by Bowen Li (200859)

“…The optimal parameters such as the width and weight of RBF are determined, and the optimal RDC-RBF fault diagnosis model is established. …”

DiagramDataLiBowen. by Bowen Li (200859)

“…The optimal parameters such as the width and weight of RBF are determined, and the optimal RDC-RBF fault diagnosis model is established. …”

Characteristic vector of indicator diagram. by Bowen Li (200859)

“…The optimal parameters such as the width and weight of RBF are determined, and the optimal RDC-RBF fault diagnosis model is established. …”

Experimental process diagram. by Bowen Li (200859)

“…The optimal parameters such as the width and weight of RBF are determined, and the optimal RDC-RBF fault diagnosis model is established. …”

Indicator diagram of pumping unit. by Bowen Li (200859)

“…The optimal parameters such as the width and weight of RBF are determined, and the optimal RDC-RBF fault diagnosis model is established. …”

RBF neural network structure diagram. by Bowen Li (200859)

“…The optimal parameters such as the width and weight of RBF are determined, and the optimal RDC-RBF fault diagnosis model is established. …”

Graphical centre of gravity. by Bowen Li (200859)

“…The optimal parameters such as the width and weight of RBF are determined, and the optimal RDC-RBF fault diagnosis model is established. …”

Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf by Muhammad Awais (263096)

“…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …”

Table_1_Air-Sea Fluxes With a Focus on Heat and Momentum.DOCX by Meghan F. Cronin (7105496)

“…To meet these targets globally, in the next decade, satellite-based observations must be optimized for boundary layer measurements of air temperature, humidity, sea surface temperature, and ocean wind stress. …”