Simulated annealing algorithm. by Muhammad Muneeb (3244095)

Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”

Calibration plot of the apparent and optimism-corrected models. by Dominika Szabo (14129304)

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

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

Score of evaluation level. by Yixuan Lu (9987980)

“…Simultaneously, based on the concept of dynamic weighting, a multiple linear regression is introduced for analyzing the weights of similar projects, resulting in the derivation of universal weights for the primary indicators within the evaluation system. …”

Expert scoring flow chart. by Yixuan Lu (9987980)

“…Simultaneously, based on the concept of dynamic weighting, a multiple linear regression is introduced for analyzing the weights of similar projects, resulting in the derivation of universal weights for the primary indicators within the evaluation system. …”

F1-score analysis of DDcGAN-GSOM with existing methods. by Nanavath Kiran Singh Nayak (22184565)

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Algorithms and evaluation metrics integrated in the COPS framework. by Teemu J. Rintala (19333003)

Schematic representation of univariate ensemble-based feature selection. by Nanavath Kiran Singh Nayak (22184565)

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Comparative analysis of DDcGAN-GSOM’s Accuracy, Precision, and F1-score. by Nanavath Kiran Singh Nayak (22184565)

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Hybrid feature selection algorithm of CSCO-ROA. by Afnan M. Alhassan (18349378)

“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”

Expert scoring values of criterion layer U₁. by Yixuan Lu (9987980)

“…Simultaneously, based on the concept of dynamic weighting, a multiple linear regression is introduced for analyzing the weights of similar projects, resulting in the derivation of universal weights for the primary indicators within the evaluation system. …”

The algorithm for the same-day surgery protocol. by Magnus Tveit (11442200)

Data_Sheet_1_Prediction of patient choice tendency in medical decision-making based on machine learning algorithm.pdf by Yuwen Lyu (14330781)

“…At the same time, the comprehensive evaluation index F1-score of the DT algorithm are 0.80, 0.61, 0.58, 0.60, the KNN algorithm are 0.75, 0.65, 0.71, 0.84, and the SVM algorithm are 0.81, 0.74, 0.73, 0.94.…”

Comparative analysis of DDcGAN-GSOM’s True Positive Rate, False Alarm Rate, and Specificity. by Nanavath Kiran Singh Nayak (22184565)

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Architecture of proposed system model. by Nanavath Kiran Singh Nayak (22184565)

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Accuracy analysis of DDcGAN-GSOM with existing techniques. by Nanavath Kiran Singh Nayak (22184565)

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Network simulation of the proposed method. by Nanavath Kiran Singh Nayak (22184565)

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