DataSheet1_Multi-Objective Optimization Design of Ladle Refractory Lining Based on Genetic Algorithm.docx حسب Ying Sun (23237)

"…<p>Genetic algorithm is widely used in multi-objective mechanical structure optimization. …"

Several loop patterns found in binary code. حسب Alba Pedro-Zapater (8600382)

Display of the bilateral BRT line in Jinan. حسب Rongrong Guo (1847989)

"…The cost includes the agency operating and user travel. The optimal design model is formulated as a mixed-integer program and solved using a fuzzy analytic hierarchy process (FAHP) and a genetic algorithm (GA). …"

Complex traffic line and track point diagram. حسب Mingkang Sun (6498791)

Complex traffic line and track point diagram. حسب Mingkang Sun (6498791)

DMTD algorithm. حسب Yunhu Huang (21402795)

"…On the basis of EITO_E, we propose EITO_P algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …"

Proposed Algorithm. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"

Genetic algorithms can be applied to higher-dimensional design problems. حسب Lu Hong (399882)

Comparisons between ADAM and NADAM optimizers. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"

Gear meshing line. حسب Linyue Qiu (17319793)

The Pseudo-Code of the IRBMO Algorithm. حسب Chenyi Zhu (9383370)

"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"

Inspection of Line Defects in Transition Metal Dichalcogenides Using a Microscopic Hyperspectral Imaging Technique حسب Xiangmin Hu (1612399)

Schematic representation of FixbbGCNs, the networks used in our experiments. حسب Jack B. Maguire (5123183)

IRBMO vs. meta-heuristic algorithms boxplot. حسب Chenyi Zhu (9383370)

"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"

IRBMO vs. feature selection algorithm boxplot. حسب Chenyi Zhu (9383370)

"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"

Easy-to-Manufacture In-Line 2D Nano Antenna for Enhanced Radiation-Cooled IR Camouflage حسب Hetao Guo (15425082)

"…Moreover, the function of the in-line 2D nano antenna is insensitive to polarization and angle incidence, which is essential for industrial use. …"

Easy-to-Manufacture In-Line 2D Nano Antenna for Enhanced Radiation-Cooled IR Camouflage حسب Hetao Guo (15425082)

"…Moreover, the function of the in-line 2D nano antenna is insensitive to polarization and angle incidence, which is essential for industrial use. …"

Easy-to-Manufacture In-Line 2D Nano Antenna for Enhanced Radiation-Cooled IR Camouflage حسب Hetao Guo (15425082)

"…Moreover, the function of the in-line 2D nano antenna is insensitive to polarization and angle incidence, which is essential for industrial use. …"

Optimization flow of trimming coefficients. حسب Weifeng Liu (635311)

"…Through a genetic algorithm, we optimize the tooth profile and tooth flank parabolic modification coefficients, resulting in optimal vibration-suppressing tooth surfaces. …"

Integration of multiple models through evolutionary multiobjective optimization improves RfaH sequence design outcomes. حسب Lu Hong (399882)