Multi objective optimization design process. by Xueyong Pan (20390363)

“…Subsequently, response surface experiments were conducted to analyze the width parameters of various flow channels in the liquid cooled plate Finally, the Design of Experiment (DOE) was employed to conduct optimal Latin hypercube sampling on the flow channel depth (<i>H</i>), mass flow (<i>Q</i>), and inlet and outlet diameter (<i>d</i>), combined with a genetic algorithm for multi-objective analysis. …”

Optimal Latin square sampling distribution. by Xueyong Pan (20390363)

“…Subsequently, response surface experiments were conducted to analyze the width parameters of various flow channels in the liquid cooled plate Finally, the Design of Experiment (DOE) was employed to conduct optimal Latin hypercube sampling on the flow channel depth (<i>H</i>), mass flow (<i>Q</i>), and inlet and outlet diameter (<i>d</i>), combined with a genetic algorithm for multi-objective analysis. …”

PANet network design. by Mengqi Yuan (4852555)

“…Finally, a bidirectional feature pyramid network (BiFPN) was integrated to optimize feature fusion, leveraging a bidirectional information transfer mechanism and an adaptive feature selection strategy. …”

The flowchart of Algorithm 2. by Jing Xu (15337)

“…To solve this optimization model, a multi-level optimization algorithm is designed. …”

BiFPN network design. by Mengqi Yuan (4852555)

“…Finally, a bidirectional feature pyramid network (BiFPN) was integrated to optimize feature fusion, leveraging a bidirectional information transfer mechanism and an adaptive feature selection strategy. …”

Design variables and range of values. by Xueyong Pan (20390363)

“…Subsequently, response surface experiments were conducted to analyze the width parameters of various flow channels in the liquid cooled plate Finally, the Design of Experiment (DOE) was employed to conduct optimal Latin hypercube sampling on the flow channel depth (<i>H</i>), mass flow (<i>Q</i>), and inlet and outlet diameter (<i>d</i>), combined with a genetic algorithm for multi-objective analysis. …”

Feasibility diagram of design points. by Xueyong Pan (20390363)

“…Subsequently, response surface experiments were conducted to analyze the width parameters of various flow channels in the liquid cooled plate Finally, the Design of Experiment (DOE) was employed to conduct optimal Latin hypercube sampling on the flow channel depth (<i>H</i>), mass flow (<i>Q</i>), and inlet and outlet diameter (<i>d</i>), combined with a genetic algorithm for multi-objective analysis. …”

The sampled values and the fitted values. by Hongjun Meng (5031806)

Sample points and numerical simulation results. by Xueyong Pan (20390363)

“…Subsequently, response surface experiments were conducted to analyze the width parameters of various flow channels in the liquid cooled plate Finally, the Design of Experiment (DOE) was employed to conduct optimal Latin hypercube sampling on the flow channel depth (<i>H</i>), mass flow (<i>Q</i>), and inlet and outlet diameter (<i>d</i>), combined with a genetic algorithm for multi-objective analysis. …”

Three sensor sample data with noise data. by Tang Ruipeng (20141334)

Simulation sample. by Xiaogang Li (299205)

Sample classes from the HMDB51 dataset. by Yasir Khan Jadoon (21433231)

Sample classes from UCF101 dataset [40]. by Yasir Khan Jadoon (21433231)

Comparative data of different soil samples. by Gourab Saha (8987405)

Data Sheet 2_Research on optimization of emergency supplies customs clearance strategy from the perspective of public health security based on Chinese trade data.zip by Xia Zheng (384416)

Data Sheet 1_Research on optimization of emergency supplies customs clearance strategy from the perspective of public health security based on Chinese trade data.zip by Xia Zheng (384416)

Train stopping plan. by Jing Xu (15337)

“…To solve this optimization model, a multi-level optimization algorithm is designed. …”

Major notations. by Jing Xu (15337)

“…To solve this optimization model, a multi-level optimization algorithm is designed. …”

S1 File - by Jing Xu (15337)

“…To solve this optimization model, a multi-level optimization algorithm is designed. …”

Image 1_A novel inversion method of slope rock mechanical parameters using differential evolution gray wolf algorithm to optimize support vector regression.tif by Tingkai Hou (21014762)

“…</p>Methods<p>This paper proposes a displacement back-analysis (DBA) approach that utilizes support vector regression (SVR) optimized by differential evolution grey wolf algorithm (DE-GWO) to invert the RMMPs, which improves global optimization capability and inversion accuracy. …”