Sensitivity values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Specificity values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Fitness values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Number of features selected for IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Classification accuracy values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

F-score values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

CSTP-MAC algorithm backoff time-slots vs IEEE 802.15.4 binary backoff exponential algorithm backoff time-slots. by Innocent Uzougbo Onwuegbuzie (9243166)

The result of the accuracy of tested algorithms. by Nebojsa Bacanin (13932723)

Subjects:

Algorithm optimization process. by Zhihao Li (359073)

“…<div><p>In order to solve the problem of poor adaptability and robustness of the rule-based energy management strategy (EMS) in hybrid commercial vehicles, leading to suboptimal vehicle economy, this paper proposes an improved dung beetle algorithm (DBO) optimized multi-fuzzy control EMS. …”

Feature selection ratio results for tested algorithms. by Nebojsa Bacanin (13932723)

Subjects:

Best fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

Subjects:

Mean fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

Subjects:

Binary contingency table. by Lu Xiao (314030)

The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. by Olaide N. Oyelade (14047002)

Subjects:

Numerical example for determining the optimal number of clusters in Algorithm 2. by Yi Wei Tye (22208735)

Standard deviation of fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

Subjects:

Optimal scheduling model of microgrid based on improved dung beetle optimization algorithm by Yu Gao (69071)

“…<p>In view of the strong uncertainty and intermittency of distributed power sources in microgrids and the shortcomings of the traditional dung beetle optimizer (DBO) algorithm with slow convergence, poor robustness and ease of falling into a local optimum, an optimal scheduling model for microgrids based on the improved dung beetle optimization algorithm is proposed. …”

DataSheet1_Improving the convergence of an iterative algorithm for solving arbitrary linear equation systems using classical or quantum binary optimization.pdf by Erick R. Castro (11243697)

a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset. by Nebojsa Bacanin (13932723)

Subjects: