Visualization of the UAVs’ movement in the cost space. حسب Quoc Bao Diep (18452207)

Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code حسب Goutami Sooda (20714729)

An overview of the organization of the study program. حسب Marialuisa Gandolfi (8639238)

الموضوعات:

Overview of the development of the biomarkers in the motor, exteroceptive, interoceptive, and cerebral domains. حسب Marialuisa Gandolfi (8639238)

الموضوعات:

The schedule of enrolment, interventions, and assessments. حسب Marialuisa Gandolfi (8639238)

الموضوعات:

Data and code resources. حسب Sam Hall-McMaster (10343795)

The Traveling Bandit: A Framework for Bayesian Optimization with Movement Costs حسب Qiyuan Chen (1570270)

"…<p>This article introduces a framework for Bayesian Optimization (BO) with metric movement costs, addressing a critical challenge in practical applications where input alterations incur varying costs. …"

The parameter setting of the evolutionary neural network. حسب Wenbing Shi (5806160)

الموضوعات:

The genome coding scheme. حسب Wenbing Shi (5806160)

الموضوعات:

The optimal number of clusters identified using the GMM clustering algorithm. حسب Dinh K. Tang (20469082)

Optimal number of clusters identified using the GMM clustering algorithm. حسب Dinh K. Tang (20469082)

Impact of multiunit merging on neural information encoding. حسب Daniel Suárez-Barrera (22676654)

الموضوعات:

Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>" حسب Yize Wang (19535173)

"…<p dir="ltr">Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>"</p>…"

Phenotype frequencies for each mutant and for complementation testing. حسب McKenna Feltes (11242085)

code_4 حسب Olga Ovtsarenko (20432033)

The first movement scenario contains two UAVs and two obstacles. حسب Quoc Bao Diep (18452207)

The second movement scenario includes five UAVs and one obstacle. حسب Quoc Bao Diep (18452207)

The third movement scenario includes ten UAVs and two obstacles. حسب Quoc Bao Diep (18452207)

The genetic algorithm. حسب Viktoria Zemliak (19500335)

IACO algorithm flowchart. حسب Pengfei Huang (552512)

"…Through case studies, we have demonstrated the superior performance of this algorithm in addressing relevant problems. The results show that, in terms of truck operational costs, the improved algorithm reduces costs by 10.96% and 3.02% compared to traditional Ant Colony Optimization and Variable Neighborhood Search algorithms, respectively, and by 4.89% compared to manual scheduling. …"