Functional fitness test results of different algorithms. by Ling Zhao (111365)

Knowledge graph model rating function. by Chunjuan Li (7890182)

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

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. …”

Rate of change of loss function (0.01, 1000, 100 runs). by Weizheng Jiang (21647509)

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. …”

A parabolic relationship between prediction errors and learning rates obtained by a cubic learning algorithm. by Boluwatife Ikwunne (22238697)

The difference between the end points of the objective function for different minimum requirement satisfaction rates. by Yuhang Wang (332111)

Algorithm Parameter Setting. by Tong Zhou (3770)

“…This strategy uses the improved D3QN algorithm combined with the excellent smoothness of the sine function to evaluate driving safety, helping vehicles find suitable gaps in traffic flow. …”

IEEE CEC 2017 benchmark function specifications. by Kankan Tang (21474968)

IEEE CEC 2022 benchmark function specifications. by Kankan Tang (21474968)

Effects of processing rate and algorithms performance on estimates of biodiversity. by Valentine Fleuré (12822137)

Experiments comparing OMWOA with alternative competing algorithms on the IEEE CEC 2017 benchmark functions. by Kankan Tang (21474968)

Experiments comparing OMWOA with alternative competing algorithms at IEEE CEC 2022 benchmark functions. by Kankan Tang (21474968)

Scalability analysis on the IEEE CEC 2017 benchmark functions. by Kankan Tang (21474968)

Box plots of different algorithms on CEC2017 functions (dim = 30,100) and CEC2022 functions (dim = 20). by Qingwen Meng (156386)

Subjects:

Algorithm operation steps. by Junyan Wang (4738518)

“…To address these issues, this paper proposes an improved object detection algorithm named SCI-YOLO11, which optimizes the YOLO11 framework from three aspects: feature extraction, attention mechanism, and loss function. …”

Evolutionary trajectory of OMWOA on the IEEE CEC 2017 benchmark functions. by Kankan Tang (21474968)

Noise decrease rate comparison. by Xianlin Ren (22783589)

Search algorithm performance comparison. by Zhaohui Du (414105)