Search alternatives:
models algorithm » mould algorithm (Expand Search), deer algorithm (Expand Search)
two algorithms » _ algorithms (Expand Search)
mesh algorithm » deer algorithm (Expand Search), search algorithm (Expand Search)
develop » developed (Expand Search)
element » elements (Expand Search)
models algorithm » mould algorithm (Expand Search), deer algorithm (Expand Search)
two algorithms » _ algorithms (Expand Search)
mesh algorithm » deer algorithm (Expand Search), search algorithm (Expand Search)
develop » developed (Expand Search)
element » elements (Expand Search)
-
141
Use of Data Mining Techniques to Detect Fraud in Procurement Sector
Published 2022“…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …”
Get full text
-
142
An efficient approach for textual data classification using deep learning
Published 2022“…<p dir="ltr">Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. …”
-
143
Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining
Published 2021“…Additionally, the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology is employed for modelling the two proposed clustering algorithms to identify transactional risks. …”
Get full text
-
144
Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…The LR model showed the foremost predictions of ground loss as compared to all the other models analyzed. …”
-
145
Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects
Published 2021“…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”
-
146
Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d...
Published 2020“…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…”
-
147
Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy
Published 2006“…This study uses the above facility in developing algorithms for digitally determining the basic pulse parameters and tackling the problem of pulse pile-up in Gamma-ray spectroscopy. …”
Get full text
Get full text
article -
148
A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text
Published 2019“…The previously published research on Arabic ontology learning from text falls into three categories: developing manually hand-crafted rules, using ordinary supervised/unsupervised machine learning algorithms, or a hybrid of these two approaches. …”
Get full text
Get full text
-
149
A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems
Published 2021“…<p>Constrained optimization plays an important role in many decision-making problems and various real-world applications. In the last two decades, various evolutionary algorithms (EAs) were developed and still are developing under the umbrella of evolutionary computation. …”
-
150
-
151
Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Published 2024“…Exploratory Data Analysis (EDA) highlights the class imbalance problem in detecting fake jobs, which tends the model to act aggressively toward the minority class. …”
-
152
Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…More specifically, we focus on studies that only fused EHR with medical imaging data to develop various AI methods for clinical applications. …”
-
153
A new family of multi-step quasi-Newton algorithms for unconstrained optimization
Published 1999“…It concentrates on deriving a variable-metric family of minimum curvature algorithms for unconstrained optimization. The derivation is based on considering a rational model, with a certain tuning parameter, where the aim is to develop a general framework that encompasses all possible two-step minimum curvature algorithms generated by appropriate parameter choices. …”
Get full text
Get full text
article -
154
A quantum algorithm for evolving open quantum dynamics on quantum computing devices
Published 2020“…<p dir="ltr">Designing quantum algorithms for simulating quantum systems has seen enormous progress, yet few studies have been done to develop quantum algorithms for open quantum dynamics despite its importance in modeling the system-environment interaction found in most realistic physical models. …”
-
155
-
156
Artificial intelligence models for predicting the mode of delivery in maternal care
Published 2025“…</p><h3>Objectives</h3><p dir="ltr">This study aims to evaluate and compare the predictive accuracy of AI algorithms in predicting the mode of delivery (vaginal or cesarean) using routinely collected antepartum data from electronic health records (EHRs). …”
-
157
Parameter Identification of Flexible Drive Systems using Particle Swarm Optimization
Published 2023Get full text
doctoralThesis -
158
Developing an online hate classifier for multiple social media platforms
Published 2020“…Although researchers have found that hate is a problem across multiple platforms, there is a lack of models for online hate detection using multi-platform data. …”
-
159
-
160
SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data
Published 2018“…This paper describes SemIndex+, a semantic-aware indexing and querying framework that allows semantic search, result selection, and result ranking of structured (relational DB-style), unstructured (IR-style), and partly structured (NoSQL) data. Various weighting functions and a parallelized search algorithm have been developed for that purpose and are presented here. …”
Get full text
Get full text
Get full text
Get full text
article