Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

“…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”

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. …”

Accuracy comparison of proposed and other models. by Subathra Gunasekaran (19492680)

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. …”

Bayesian sequential design for sensitivity experiments with hybrid responses by Yuxia Liu (1779592)

“…To deal with the problem of complex computation involved in searching for optimal designs, fast algorithms are presented using two strategies to approximate the optimal criterion, denoted as SI-optimal design and Bayesian D-optimal design, respectively. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

Optimized model prediction performance. by Guang Tu (22054865)

MLP vs classification algorithms. by Mohd Mustaqeem (19106494)

“…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”

Data_Sheet_1_Optimizing Spatio-Temporal Allocation of the COVID-19 Vaccine Under Different Epidemiological Landscapes.pdf by Wen Cao (696121)

Data_Sheet_1_Phase-wise evaluation and optimization of non-pharmaceutical interventions to contain the COVID-19 pandemic in the U.S..pdf by Xiao Zhou (122661)

SBM 2023 Poster: Development and Validation of Multivariable Prediction Algorithms to Estimate Future Walking Behavior in Adults: Retrospective Cohort Study by Junghwan Park (15195436)

“…MLP also showed superior overall performance to all other tried algorithms in MCC (0.643±0.021), sensitivity (86.1±3.0%), and specificity (77.8±3.3%).…”

Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection by Samin Aref (4683934)

“…</p><p dir="ltr">This dataset is provided under a CC BY-NC-SA Creative Commons v 4.0 license (Attribution-NonCommercial-ShareAlike). This means that other individuals may remix, tweak, and build upon these data non-commercially, as long as:</p><p dir="ltr">1) They provide citations to this data repository (<a href="https://doi.org/10.6084/m9.figshare.28835837" rel="noreferrer" target="_blank">https://doi.org/10.6084/m9.figshare.28835837</a>) and the following article: Aref S, Ng B (2025) Troika algorithm: Approximate optimization for accurate clique partitioning and clustering of weighted networks. …”

Data_Sheet_2_Decision Tree With Only Two Musculoskeletal Sites to Diagnose Polymyalgia Rheumatica Using [18F]FDG PET-CT.docx by Anthime Flaus (10153055)

Data_Sheet_1_Decision Tree With Only Two Musculoskeletal Sites to Diagnose Polymyalgia Rheumatica Using [18F]FDG PET-CT.docx by Anthime Flaus (10153055)