Table 6_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx by Peng Zhu (277243)

“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”

Statistical results of various algorithms. by ZeSheng Lin (20501356)

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Comparison of average precision means of different algorithms. by Haisong Xu (141729)

Algorithm comparison experiment on the RSOD dataset. by Pingping Yan (462509)

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ANOVA was performed to test the differences between the algorithms for each indicator. by Jihui Hu (19812736)

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Descriptions of the selected CEC 2017 benchmark functions. by ZeSheng Lin (20501356)

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Descriptions of the selected CEC 2005 benchmark functions. by ZeSheng Lin (20501356)

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Descriptions of the selected CEC 2022 benchmark functions. by ZeSheng Lin (20501356)

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Heatmap results from the global sensitivity analysis for the generation of villous vessels within a placentone. by Diana C. de Oliveira (9220729)

The phase-field function for three different network configurations considered in this work. by Martina Bukač (20161460)

Efficient Algorithms for GPU Accelerated Evaluation of the DFT Exchange-Correlation Functional by Ryan Stocks (16867476)

“…Improving algorithmic efficiency through hardware-aware implementations enables application to larger systems and more efficient generation of larger training data sets for machine-learning. …”

PSO parameters and objective function. by André G. Coimbra (21354135)

GA parameters and objective function. by André G. Coimbra (21354135)

Parameterization of the feature selection algorithm. by Chenyi Zhu (9383370)

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Comparison of metaheuristic algorithm parameterization. by Chenyi Zhu (9383370)

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

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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. …”