Algorithm optimization process. حسب Zhihao Li (359073)

Sensitivity values of IRBMO vs. other binary algorithms. حسب Chenyi Zhu (9383370)

Specificity values of IRBMO vs. other binary algorithms. حسب Chenyi Zhu (9383370)

Fitness values of IRBMO vs. other binary algorithms. حسب Chenyi Zhu (9383370)

Number of features selected for IRBMO vs. other binary algorithms. حسب Chenyi Zhu (9383370)

Classification accuracy values of IRBMO vs. other binary algorithms. حسب Chenyi Zhu (9383370)

F-score values of IRBMO vs. other binary algorithms. حسب Chenyi Zhu (9383370)

Coarse-fine optimization algorithm. حسب Chao Ma (207385)

"…To improve the focusing efficiency and optimize the focusing process, a search strategy combining a climbing search algorithm and a traversal method was proposed. …"

Final solution set for overspeed protection for gas turbine problem (termination condition is 500 iteration). حسب Heba Askr (15572851)

Final solution set for a series-parallel system with five subsystems (termination condition is 500 iteration). حسب Heba Askr (15572851)

Proposed Algorithm. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

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. …"

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

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

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. …"

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. …"

Material parameters. حسب Dapeng Wang (250459)

"…The impact of detection probability and maintenance measures on the service life of tunnel lining and the cost of detection and maintenance of cracked lining in the whole life cycle was analyzed; the optimization calculation model of tunnel lining crack detection and maintenance strategy based on genetic algorithm was established with the multi-objective optimization function of maximizing the service life of detection and maintenance and minimizing the total cost of detection and maintenance of fatigue cracks. …"

S1 File - حسب Dapeng Wang (250459)

"…The impact of detection probability and maintenance measures on the service life of tunnel lining and the cost of detection and maintenance of cracked lining in the whole life cycle was analyzed; the optimization calculation model of tunnel lining crack detection and maintenance strategy based on genetic algorithm was established with the multi-objective optimization function of maximizing the service life of detection and maintenance and minimizing the total cost of detection and maintenance of fatigue cracks. …"

Parameter values. حسب Dapeng Wang (250459)

"…The impact of detection probability and maintenance measures on the service life of tunnel lining and the cost of detection and maintenance of cracked lining in the whole life cycle was analyzed; the optimization calculation model of tunnel lining crack detection and maintenance strategy based on genetic algorithm was established with the multi-objective optimization function of maximizing the service life of detection and maintenance and minimizing the total cost of detection and maintenance of fatigue cracks. …"

PoD of cracks by ultrasonic method. حسب Dapeng Wang (250459)

"…The impact of detection probability and maintenance measures on the service life of tunnel lining and the cost of detection and maintenance of cracked lining in the whole life cycle was analyzed; the optimization calculation model of tunnel lining crack detection and maintenance strategy based on genetic algorithm was established with the multi-objective optimization function of maximizing the service life of detection and maintenance and minimizing the total cost of detection and maintenance of fatigue cracks. …"

Time course curve of SIFs. حسب Dapeng Wang (250459)

"…The impact of detection probability and maintenance measures on the service life of tunnel lining and the cost of detection and maintenance of cracked lining in the whole life cycle was analyzed; the optimization calculation model of tunnel lining crack detection and maintenance strategy based on genetic algorithm was established with the multi-objective optimization function of maximizing the service life of detection and maintenance and minimizing the total cost of detection and maintenance of fatigue cracks. …"