Sensor value scenario for average value algorithm. by Gourab Saha (8987405)

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Sensor value scenario for fuzzy logic algorithm. by Gourab Saha (8987405)

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The final values of the cost function, the selected features number, and the implementation time for the introduced meta-heuristic algorithms. by Hamed Khodadadi (21446172)

“…<p>The final values of the cost function, the selected features number, and the implementation time for the introduced meta-heuristic algorithms.…”

The function value of the single objective optimal solution. by Yuhang Wang (332111)

wIRBMO feature selection algorithm improving rate. by Chenyi Zhu (9383370)

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Water consumption due to average value and fuzzy logic algorithm. by Gourab Saha (8987405)

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DE algorithm flow. by Ling Zhao (111365)

“…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …”

Test results of different algorithms. by Ling Zhao (111365)

“…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …”

Comparison of average precision mean and loss function for different models. by Ting Wang (16292)

Completion times for different algorithms. by Jianbin Zheng (587000)

“…Action masking is used to filter out invalid states and actions, while a shared reward mechanism is adopted to balance cooperation efficiency among agents. Additionally, value function normalization and adaptive learning rate strategies are applied to accelerate convergence. …”

The average cumulative reward of algorithms. by Jianbin Zheng (587000)

“…Action masking is used to filter out invalid states and actions, while a shared reward mechanism is adopted to balance cooperation efficiency among agents. Additionally, value function normalization and adaptive learning rate strategies are applied to accelerate convergence. …”

RMSE value of different missing rates on UCI Heart dataset. by Xing Chen (140292)

Loss function curve graphs. by Huiying Zhang (200681)

Reward function related parameters. by Honglei Pang (22693724)

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Comparative experimental data of loss functions. by Huiying Zhang (200681)

“…Experimental results show that the detection accuracy of 78% for small infrared nighttime targets, with a recall rate of 58.6%, an mAP value of 67%. and a parameter count of 20.9M for the MDCFVit-YOLO model. …”

Simulation settings of rMAPPO algorithm. by Jianbin Zheng (587000)

“…Action masking is used to filter out invalid states and actions, while a shared reward mechanism is adopted to balance cooperation efficiency among agents. Additionally, value function normalization and adaptive learning rate strategies are applied to accelerate convergence. …”

Filled contour plot based on histograms of the occurence-frequency of binned values of and as a function of rate ratio . by Paul Kinsler (3975620)

Comparison of the curves of the DCIOU loss function and the CIOU loss function. by Xunqian Xu (21261899)

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Multimodal reference functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Evaluation metrics graphs for different loss functions. by Huiying Zhang (200681)