Search alternatives:
driven optimization » guided optimization (Expand Search), dose optimization (Expand Search), process optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
final sampling » final sample (Expand Search), field sampling (Expand Search), edna sampling (Expand Search)
binary ips » binary pairs (Expand Search)
ips driven » i driven (Expand Search), us driven (Expand Search), ngs driven (Expand Search)
driven optimization » guided optimization (Expand Search), dose optimization (Expand Search), process optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
final sampling » final sample (Expand Search), field sampling (Expand Search), edna sampling (Expand Search)
binary ips » binary pairs (Expand Search)
ips driven » i driven (Expand Search), us driven (Expand Search), ngs driven (Expand Search)
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41
Results of ablation experiments.
Published 2025“…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. …”
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42
Image of the ReLU function.
Published 2025“…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. …”
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43
Plot of baseline model output results.
Published 2025“…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. …”
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44
Comparative test results.
Published 2025“…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. …”
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45
Recall results.
Published 2025“…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. …”
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46
mAP@0.5:0.95 results.
Published 2025“…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. …”
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47
Precision results.
Published 2025“…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. …”
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48
SimConv structure.
Published 2025“…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. …”
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49
Table of training hyperparameters.
Published 2025“…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. …”
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50
Diagram of the original model confusion matrix.
Published 2025“…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. …”
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51
Orthogonal experiment scheme and results.
Published 2024“…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. …”
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52
Comparison of precision of various proxy models.
Published 2024“…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. …”
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53
Comparison between actual and predicted values.
Published 2024“…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. …”
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54
Three-dimensional heat transfer model parameters.
Published 2024“…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. …”
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55
2C discharge rate grid independence test.
Published 2024“…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. …”
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56
Related parameters of square LIBs.
Published 2024“…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. …”
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57
Battery pack model.
Published 2024“…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. …”
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58
MCLP_quantum_annealer_V0.5
Published 2025“…This paper first proposes the QUBO-MCLP algorithm workflow and designs the Transformation Operator for Inequality Constraints Considering the Capacity of Accessible Providers (TOICCAP), which accounts for the scale of accessible supply points. …”
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59
Table 8_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx
Published 2025“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”
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60
Table 5_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx
Published 2025“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”