Search alternatives:
process optimization » model optimization (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
process optimization » model optimization (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
-
81
-
82
Summary of literature review.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
-
83
Topic description.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
-
84
Notations along with their descriptions.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
-
85
Detail of the topics extracted from DUC2002.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
-
86
Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx
Published 2022“…</p>Materials and Methods<p>Leveraging data from electronic healthcare records and a unique MDRO universal screening program, we developed a data-driven modeling framework to predict MRSA, VRE, and CRE colonization upon intensive care unit (ICU) admission, and identified the associated socio-demographic and clinical factors using logistic regression (LR), random forest (RF), and XGBoost algorithms. …”
-
87
-
88
-
89
Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish)
Published 2024“…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …”
-
90
GSE96058 information.
Published 2024“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
-
91
The performance of classifiers.
Published 2024“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
-
92
-
93
PathOlOgics_RBCs Python Scripts.zip
Published 2023“…This process generated a ground-truth binary semantic segmentation mask and determined the bounding box coordinates (XYWH) for each cell. …”
-
94
Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
Published 2019“…This result reflects the effectiveness of the algorithm, which provides a basis for the effective analysis and processing of image big data.…”
-
95
-
96
-
97
Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png
Published 2025“…RSEE projects heterogeneous input data into an exertion-conditioned latent space, aligning model predictions with observed physiological variance and mitigating false positives by explicitly modeling the overlap between athletic remodeling and subclinical pathology.…”
-
98
Contextual Dynamic Pricing with Strategic Buyers
Published 2024“…<p>Personalized pricing, which involves tailoring prices based on individual characteristics, is commonly used by firms to implement a consumer-specific pricing policy. In this process, buyers can also strategically manipulate their feature data to obtain a lower price, incurring certain manipulation costs. …”
-
99
DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). …”
-
100