Search alternatives:
complex optimization » convex optimization (Expand Search), whale optimization (Expand Search), wolf optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
binary primate » binary image (Expand Search)
primate codon » primate model (Expand Search)
based complex » layer complex (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
complex optimization » convex optimization (Expand Search), whale optimization (Expand Search), wolf optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
binary primate » binary image (Expand Search)
primate codon » primate model (Expand Search)
based complex » layer complex (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
-
121
RSF Components of the best five individuals.
Published 2024“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”
-
122
Open loop simulation.
Published 2024“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”
-
123
Average wind test fitness.
Published 2024“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”
-
124
Internal process of a policy gradient block.
Published 2024“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”
-
125
Training process of a DDPG individual.
Published 2024“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”
-
126
PbGA search phases to find the best individuals.
Published 2024“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”
-
127
Previous usages of DRL in solving PDG problems.
Published 2024“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”
-
128
Internal process of a critic gradient block.
Published 2024“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”
-
129
Best Individuals from the mapping phase.
Published 2024“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”
-
130
Schematic diagram of weld surface defects.
Published 2024“…<div><p>The background of pipeline weld surface defect image is complex, and the defect size is small. Aiming at the small defect size in the weld image, which is easy to cause missed detection and false detection, a lightweight target detection algorithm based on improved YOLOv7 is proposed. …”
-
131
Improved YOLOv7 network structure.
Published 2024“…<div><p>The background of pipeline weld surface defect image is complex, and the defect size is small. Aiming at the small defect size in the weld image, which is easy to cause missed detection and false detection, a lightweight target detection algorithm based on improved YOLOv7 is proposed. …”
-
132
Renderings of data enhancements.
Published 2024“…<div><p>The background of pipeline weld surface defect image is complex, and the defect size is small. Aiming at the small defect size in the weld image, which is easy to cause missed detection and false detection, a lightweight target detection algorithm based on improved YOLOv7 is proposed. …”
-
133
Number and size of marked defects.
Published 2024“…<div><p>The background of pipeline weld surface defect image is complex, and the defect size is small. Aiming at the small defect size in the weld image, which is easy to cause missed detection and false detection, a lightweight target detection algorithm based on improved YOLOv7 is proposed. …”
-
134
Loss function curve.
Published 2024“…<div><p>The background of pipeline weld surface defect image is complex, and the defect size is small. Aiming at the small defect size in the weld image, which is easy to cause missed detection and false detection, a lightweight target detection algorithm based on improved YOLOv7 is proposed. …”
-
135
Precision-Recall curve.
Published 2024“…<div><p>The background of pipeline weld surface defect image is complex, and the defect size is small. Aiming at the small defect size in the weld image, which is easy to cause missed detection and false detection, a lightweight target detection algorithm based on improved YOLOv7 is proposed. …”
-
136
Comparison experiment results.
Published 2024“…<div><p>The background of pipeline weld surface defect image is complex, and the defect size is small. Aiming at the small defect size in the weld image, which is easy to cause missed detection and false detection, a lightweight target detection algorithm based on improved YOLOv7 is proposed. …”
-
137
Ablation experiment results.
Published 2024“…<div><p>The background of pipeline weld surface defect image is complex, and the defect size is small. Aiming at the small defect size in the weld image, which is easy to cause missed detection and false detection, a lightweight target detection algorithm based on improved YOLOv7 is proposed. …”
-
138
Deepwise separable convolution structure diagram.
Published 2024“…<div><p>The background of pipeline weld surface defect image is complex, and the defect size is small. Aiming at the small defect size in the weld image, which is easy to cause missed detection and false detection, a lightweight target detection algorithm based on improved YOLOv7 is proposed. …”
-
139
DataSheet_2_Predicting non-native seaweeds global distributions: The importance of tuning individual algorithms in ensembles to obtain biologically meaningful results.docx
Published 2022“…Inspecting the number of predictors to include in final ensembles and the selection of algorithms and its complexity have been demonstrated to be crucial for this purpose. …”
-
140
DataSheet_3_Predicting non-native seaweeds global distributions: The importance of tuning individual algorithms in ensembles to obtain biologically meaningful results.zip
Published 2022“…Inspecting the number of predictors to include in final ensembles and the selection of algorithms and its complexity have been demonstrated to be crucial for this purpose. …”