Experimental results of cantilever beam design. by Qingwen Meng (156386)

“…This mechanism ensures that individuals that fail to update have a certain probability of being retained in the next generation population, while guaranteeing that the current global optimal solution remains unchanged, thereby accelerating the algorithm’s convergence. The ASBOA algorithm was evaluated using the CEC2017 and CEC2022 benchmark test functions and compared with other algorithms (such as PSO, GWO, DBO, and CPO). …”

-value on CEC2017 (dim = 30). by Qingwen Meng (156386)

“…This mechanism ensures that individuals that fail to update have a certain probability of being retained in the next generation population, while guaranteeing that the current global optimal solution remains unchanged, thereby accelerating the algorithm’s convergence. The ASBOA algorithm was evaluated using the CEC2017 and CEC2022 benchmark test functions and compared with other algorithms (such as PSO, GWO, DBO, and CPO). …”

Statistics of WSN experiment results. by Qingwen Meng (156386)

“…This mechanism ensures that individuals that fail to update have a certain probability of being retained in the next generation population, while guaranteeing that the current global optimal solution remains unchanged, thereby accelerating the algorithm’s convergence. The ASBOA algorithm was evaluated using the CEC2017 and CEC2022 benchmark test functions and compared with other algorithms (such as PSO, GWO, DBO, and CPO). …”

-value on CEC2022 (dim = 20). by Qingwen Meng (156386)

“…This mechanism ensures that individuals that fail to update have a certain probability of being retained in the next generation population, while guaranteeing that the current global optimal solution remains unchanged, thereby accelerating the algorithm’s convergence. The ASBOA algorithm was evaluated using the CEC2017 and CEC2022 benchmark test functions and compared with other algorithms (such as PSO, GWO, DBO, and CPO). …”

Experimental results of three-bar truss design. by Qingwen Meng (156386)

“…This mechanism ensures that individuals that fail to update have a certain probability of being retained in the next generation population, while guaranteeing that the current global optimal solution remains unchanged, thereby accelerating the algorithm’s convergence. The ASBOA algorithm was evaluated using the CEC2017 and CEC2022 benchmark test functions and compared with other algorithms (such as PSO, GWO, DBO, and CPO). …”

Stretch/compress spring structure. by Qingwen Meng (156386)

“…This mechanism ensures that individuals that fail to update have a certain probability of being retained in the next generation population, while guaranteeing that the current global optimal solution remains unchanged, thereby accelerating the algorithm’s convergence. The ASBOA algorithm was evaluated using the CEC2017 and CEC2022 benchmark test functions and compared with other algorithms (such as PSO, GWO, DBO, and CPO). …”

Demonstration of the limitations of existing spatial analysis methods, namely nearest neighbor distance (NND), G-cross function and Morisita-Horn index. by Mai Chan Lau (3135303)

The GA iteration result. by Jiaqing Huang (5018492)

“…This study proposes a hybrid model—Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)—to enhance bank risk identification within this context. …”

GA crossover and mutation process. by Jiaqing Huang (5018492)

“…This study proposes a hybrid model—Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)—to enhance bank risk identification within this context. …”

The framework for the proposed model and GA-FNN. by Jiaqing Huang (5018492)

“…This study proposes a hybrid model—Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)—to enhance bank risk identification within this context. …”

The structure for the FNN. by Jiaqing Huang (5018492)

“…This study proposes a hybrid model—Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)—to enhance bank risk identification within this context. …”

Adaptive grid based moving mesh algorithms for singularly perturbed second-order Volterra integro differential equations by Sushree Priyadarshana (21752424)

“…A well-studied first-order monitor function is used to construct Scheme-I which is a combination of the upwind scheme and the left rectangle rule of first-order accuracy. …”

The enrichplot of ssGSEA for CCNB1, CXCL10, DEFA4, IL7R, NCAPG and PRTN3. by Rui Guo (134395)

Analysis of HK2-<i>SOX10</i> mRNA interaction. by Ana Luisa Dian (22258504)

Predicted structure of VPS13C PD variants. by Anna K. Waldmann (22250729)

Degree 5 algorithm from Recovering the cluster picture of a polynomial over a discretely valued field by Lilybelle Cowland Kellock (20938306)

MCLP_quantum_annealer_V0.5 by Anonymous Anonymous (4854526)

“…The results demonstrate the effectiveness of the QUBO-MCLP algorithm workflow, with TOICCAP successfully converting slack variables in inequality-constrained functions for p>2, and LTOICCAP effectively reducing the number of linear and quadratic variables. …”

Data Sheet 1_Assessment of shoulder functional movements through inertial measurement units for tele-rehabilitation: a quaternion-based approach.pdf by Matteo Iurato (22155370)

“…Outputs from the application of the proposed methodology on collected data from same or different movements were statistically compared, revealing ability of discriminating repetitions of the same or of different movements (p<0.01, rrb effect size = 0.97, contrast ratio 1.7). The proposed algorithm was also confronted with the traditional approaches by statistically comparing outputs from comparison matrices rescaled in equal range of values, and results indicated mild differences in performance (rrb effect size < 0.5). …”

Automated Analysis of Astrocyte Cell Connectivity After Laser Ablation Using Machine Learning and Path-Finding Algorithms by Connor Lee (22327243)

Decoding motor patterns as a function of word length. by Viet Chau Linh Nguyen (21601707)

“…(C) Average number of fixations in good (blue dots) and poor decoders (red dots) as a function of word length (expressed in number of characters) in both training sessions. …”