Search alternatives:
processing algorithm » processing algorithms (Expand Search)
modeling algorithm » scheduling algorithm (Expand Search)
data modeling » data models (Expand Search), spatial modeling (Expand Search)
rd algorithm » _ algorithms (Expand Search)
elements rd » elements _ (Expand Search)
processing algorithm » processing algorithms (Expand Search)
modeling algorithm » scheduling algorithm (Expand Search)
data modeling » data models (Expand Search), spatial modeling (Expand Search)
rd algorithm » _ algorithms (Expand Search)
elements rd » elements _ (Expand Search)
-
321
Stability and Numerical Solutions of Second Wave Mathematical Modeling on COVID-19 and Omicron Outbreak Strategy of Pandemic: Analytical and Error Analysis of Approximate Series So...
Published 2022“…<p dir="ltr">This paper deals with the mathematical modeling of the second wave of COVID-19 and verifies the current Omicron variant pandemic data in India. …”
-
322
Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring
Published 2024“…<h3>Background and Motivations</h3><p dir="ltr">Physiological signals, such as the Photoplethysmogram (PPG) collected through wearable devices, consistently encounter significant motion artifacts. Current signal processing techniques, and even state-of-the-art machine learning algorithms, frequently struggle to effectively restore the inherent bodily signals amidst the array of randomly generated distortions. …”
-
323
Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
Published 2019Get full text
doctoralThesis -
324
Predicting Plasma Vitamin C Using Machine Learning
Published 2022“…The low R-squared scores obtained by the models are likely to be due to the low resolution of the NHANES data, particularly the dietary data. …”
-
325
Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers
Published 2024“…In particular, Isolation Forest (iForest) was applied as an anomaly detection algorithm to address class imbalance. iForest was trained on the control group data to detect cases of high risk for T2DM development as outliers. …”
Get full text
-
326
-
327
-
328
LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications
Published 2024Get full text
article -
329
Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles
Published 2017“…The identified a priori knowledge is used to implement an optimal Kalman filter, a multi-hypothesis Kalman filter, and a variant of the full information estimator (moving horizon estimator) to the problem at hand. The proposed algorithms are initially deployed in a simulation environment, and then the experimental data sets are fed into the algorithms to validate their performance. …”
Get full text
article -
330
Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model
Published 2024“…The proposed approach of DDN is trained with proper data sequences used for communication and the training phase is conducted with the norms of numerous channel variants. …”
-
331
HVAC system attack detection dataset
Published 2021“…It aims to promote and support the research in the field of cybersecurity of HVAC systems in smart buildings by facilitating the validation of attack detection and mitigation strategies, benchmarking the performance of different data-driven algorithms, and studying the impact of attacks on the HVAC system.…”
-
332
Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications
Published 2025“…In interpreting these results, it is important to consider modelling uncertainties, including assumptions and data limitations.…”
-
333
Intelligent Bilateral Client Selection in Federated Learning Using Game Theory
Published 2022“…Adopting a random selection strategy would entail substantial problems due to the heterogeneity in terms of data quality, and computational and communication resources across the participants. …”
Get full text
Get full text
Get full text
masterThesis -
334
Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems
Published 2023“…First, a feature selection tool using PSO Algorithm is developed. Then, in order to maximize the diversity between data samples and improve the effectiveness of using PSO algorithm for feature selection, the Euclidean distance metric is used in order to reduce the data and maximize the diversity between data samples. …”
-
335
Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks
Published 2023“…The algorithm was stationed at each monitoring node using interacting multiple model (IMM)-based fusion architecture. …”
-
336
Scatter search metaheuristic for homology based protein structure prediction. (c2015)
Published 2015“…We assess our algorithm on a total of 11 proteins whose structures are present in the Protein Data Bank (PDB) and which has been used in previous literature. …”
Get full text
Get full text
masterThesis -
337
A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition
Published 2025“…The proposed method divides multiple regions (different data lengths) into the feature space, allowing the algorithm to learn more complex decision boundaries. …”
-
338
-
339
Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma
Published 2019“…<h3>Background</h3><p dir="ltr">Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. …”
-
340
Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
Published 2024“…Furthermore, future studies could evaluate more efficient modeling algorithms, especially those combining topic modeling with statistical uncertainty quantification, such as conformal prediction.…”