F9 function and convergence curve graph. by Jiangli Yu (4601986)

F2 function and convergence curve graph. by Jiangli Yu (4601986)

F8 function and convergence curve graph. by Jiangli Yu (4601986)

F3 function and convergence curve graph. by Jiangli Yu (4601986)

Cost function coefficients for all CHPs in MMGs. by Hamid Amini Khanavandi (19267750)

libEnsemble: New capabilities for coordinating dynamic ensembles of calculations by John-Luke Navarro (9024008)

The distribution function graphs of prediction errors for CLPREM model and its comparative models in three different environments, as well as the root mean square error of predicti... by Xiaorui Wu (8322705)

We recorded the distribution function of the one-step prediction time for CLPREM and its comparative models, as well as a curve graph showing the multiple of the comparative model’... by Xiaorui Wu (8322705)

Complementary cumulative distribution functions of in degree distribution and fitted power law, lognormal and truncated power law distributions. by Olga Valba (10531121)

Image of the ReLU function. by Mengqi Yuan (4852555)

Mean convergence graphs of the evolution in the performance function and its terms through generations in thirty executions of each algorithm. by Roberto Castro-Medina (21484990)

“…<p>Mean convergence graphs of the evolution in the performance function and its terms through generations in thirty executions of each algorithm.…”

S1 File - by Yuh-Chin T. Huang (17867207)

“…In this study, we developed a computerized algorithm using the python package (pdfplumber) and validated against clinicians’ interpretation. …”

S1 Dataset - by Yuh-Chin T. Huang (17867207)

“…In this study, we developed a computerized algorithm using the python package (pdfplumber) and validated against clinicians’ interpretation. …”

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

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

Available functions in the utility package. by Raul Castañeda (13932971)

Disentangling the Contribution of Each Descriptive Characteristic of Every Single Mutation to Its Functional Effects by C. K. Sruthi (5391104)

Disentangling the Contribution of Each Descriptive Characteristic of Every Single Mutation to Its Functional Effects by C. K. Sruthi (5391104)

Iteration Vs fitness function. by Ajmeera Kiran (16819294)

Route for bays29 output by ABSQL algorithm. by Jin Zhang (53297)

“…DSRABSQL builds upon the Q-learning (QL) algorithm. Considering its problems of slow convergence and low accuracy, four strategies within the QL framework are designed first: the weighting function-based reward matrix, the power function-based initial Q-table, a self-adaptive <i>ε-beam</i> search strategy, and a new Q-value update formula. …”