Search alternatives:
modeling algorithm » scheduling algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
data modeling » data models (Expand Search), spatial modeling (Expand Search)
modeling algorithm » scheduling algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
data modeling » data models (Expand Search), spatial modeling (Expand Search)
-
121
Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…The outcomes revealed that these ML algorithms can be useful in predicting ground losses during wild blueberry harvesting in the selected fields.…”
-
122
-
123
Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
Published 2022Subjects: -
124
QU-GM: An IoT Based Glucose Monitoring System From Photoplethysmography, Blood Pressure, and Demographic Data Using Machine Learning
Published 2024“…Furthermore, the proposed models were deployed in Amazon Web Server. The wristband is connected to an Android mobile application to collect real-time data and update the estimated glucose and diabetic severity every 10-seconds, which will allow the users to gain better control of their diabetic health.…”
-
125
A comparison of data mapping algorithms for parallel iterative PDE solvers
Published 1995“…We review and evaluate the performances of six data mapping algorithms used for parallel single-phase iterative PDE solvers with irregular 2-dimensional meshes on multicomputers. …”
Get full text
Get full text
Get full text
article -
126
An enhanced k-means clustering algorithm for pattern discovery in healthcare data
Published 2015“…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …”
Get full text
Get full text
Get full text
Get full text
article -
127
-
128
-
129
Information reconciliation through agent controlled graph model. (c2018)
Published 2018“…Multiple models have been proposed and different techniques and data structures were used. …”
Get full text
Get full text
Get full text
masterThesis -
130
The use of multi-task learning in cybersecurity applications: a systematic literature review
Published 2024“…Five critical applications, such as network intrusion detection and malware detection, were identified, and several tasks used in these applications were observed. Most of the studies used supervised learning algorithms, and there were very limited studies that focused on other types of machine learning. …”
-
131
Label dependency modeling in Multi-Label Naïve Bayes through input space expansion
Published 2024“…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. …”
-
132
XBeGene: Scalable XML Documents Generator by Example Based on Real Data
Published 2012“…Inspired by the query-by-example paradigm in information retrieval, Our generator system i)allows the user to provide her own sample XML documents as input, ii) analyzes the structure, occurrence frequencies, and content distributions for each XML element in the user input documents, and iii) produces synthetic XML documents which closely concur, in both structural and content features, to the user's input data. …”
Get full text
Get full text
Get full text
Get full text
conferenceObject -
133
-
134
Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…The most important question when using multimodal data is how to fuse them—a field of growing interest among researchers. …”
-
135
Data Endowment as a Digital Waqf: An Islamic Ethical Framework for AI Development
Published 2025“…<p dir="ltr">In the era of artificial intelligence (AI), data is often called the new oil—an essential asset for training algorithms and fueling intelligent systems. …”
-
136
A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm
Published 2023“…The t-test and the binary whale optimization algorithm (BWOA) were applied to choose the best features and train the support vector machine (SVM) model with validation and training data. …”
-
137
-
138
-
139
Genetic and heuristic algorithms for regrouping service sites. (c2000)
Published 2000Get full text
Get full text
masterThesis -
140
Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System
Published 2021“…We research and test the design of the right neural networks that achieves our goal. A modern algorithm was improvised for this reason. For our proposed recommendation system, a database program was created to store data and include details in the analysis of course learning outcomes. …”
Get full text
Get full text