The Pseudo-Code of the IRBMO Algorithm. by 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. …”

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

“…<b>(B)</b> Focusing on the positive class only, the algorithm exploits FIM (<i>apriori</i> algorithm) to build a list of candidate interactions of any desired order, retaining those that have an empirical frequency above a given threshold <i>δ</i>. …”

The illustration depicts our CQ-CNN architecture for binary image classification. by Mominul Islam (3513758)

Statistical summary of all models. by Amal H. Alharbi (21755906)

“…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”

Classification performance of ML and DL models. by Amal H. Alharbi (21755906)

“…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”

Application of ABC SMC to the fitting of the binary flip with cusp model. by Elena Camacho-Aguilar (10906327)

IRBMO vs. meta-heuristic algorithms boxplot. by 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. …”

IRBMO vs. feature selection algorithm boxplot. by 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. …”

Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations. by Tristan Mary-Huard (3864)

“…<p>(a) The starting tree corresponds to the independent-descent model, and has all populations directly connected to ancestral Population 0. …”

ROC curve for binary classification. by Nicodemus Songose Awarayi (18414494)

“…The model was trained and evaluated using a 10-fold cross-validation sampling approach with a learning rate of 0.001 and 200 training epochs at each instance. …”

Confusion matrix for binary classification. by Nicodemus Songose Awarayi (18414494)

“…The model was trained and evaluated using a 10-fold cross-validation sampling approach with a learning rate of 0.001 and 200 training epochs at each instance. …”

Classification performance after optimization. by Amal H. Alharbi (21755906)

“…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”

ANOVA test for optimization results. by Amal H. Alharbi (21755906)

“…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”

Wilcoxon test results for optimization. by Amal H. Alharbi (21755906)

“…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”

Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data by Changhun Kim (682542)

“…In addition, hyperparameter tuning of the RF algorithm significantly improved F1 on CI assays. This study provided a basis for developing a toxicity classification model with improved performance by evaluating the effects of data set characteristics. …”

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

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Ablation test results. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Hyperparameter selection test. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

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

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Backtracking strategy diagram. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”