Radial dendrogram obtained from DBHT algorithm with Kendall’ <i>τ</i> correlation distance and generalization error similarity. حسب Luan Carlos de Sena Monteiro Ozelim (16914117)

الموضوعات:

MonteCat: A Basin-Hopping-Inspired Catalyst Descriptor Search Algorithm for Machine Learning Models حسب Fernando Garcia-Escobar (14835006)

"…Herein, a small descriptor-engineered data set containing 3289 descriptor variables and the performance of 200 catalysts for the oxidative coupling of methane (OCM) is analyzed, and a descriptor search algorithm based on the workflow of the Basin-hopping optimization methodology is proposed to select the descriptors that better fit a predictive model. …"

Parameter settings of the comparison algorithms. حسب Ying Li (38224)

"…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …"

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(1,1), i.e., uniform distribution over the interval, according to thei... حسب Luan Carlos de Sena Monteiro Ozelim (16914117)

الموضوعات:

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. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"

Efficient estimation of generalized linear latent variable models حسب Jenni Niku (6655583)

"…To fill this gap, we show in this paper how to obtain computationally convenient estimation algorithms based on a combination of either the Laplace approximation method or variational approximation method, and automatic optimization techniques implemented in R software. …"

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(2,2), i.e., the center of mass of the distribution at the center of t... حسب Luan Carlos de Sena Monteiro Ozelim (16914117)

الموضوعات:

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(5,2), i.e., the center of mass of the distribution closer to the righ... حسب Luan Carlos de Sena Monteiro Ozelim (16914117)

الموضوعات:

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(2,5), i.e., the center of mass of the distribution closer to the left... حسب Luan Carlos de Sena Monteiro Ozelim (16914117)

الموضوعات:

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. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"

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. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(0.5,0.5), i.e., two centers of mass for the distribution located at b... حسب Luan Carlos de Sena Monteiro Ozelim (16914117)

الموضوعات:

The fitting results each model. حسب Chengxin Yin (17283226)

Plan frame of the house. حسب Ling Zhao (111365)

"…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …"

Ablation test results. حسب Ling Zhao (111365)

"…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …"

Hyperparameter selection test. حسب Ling Zhao (111365)

"…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …"

Multiple index test results of different methods. حسب Ling Zhao (111365)

"…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …"

Backtracking strategy diagram. حسب Ling Zhao (111365)

"…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …"

Comparison of differences in literature methods. حسب Ling Zhao (111365)

"…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …"

New building interior space layout model flow. حسب Ling Zhao (111365)

"…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …"