Search alternatives:
processing algorithm » processing algorithms (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
end processing » text processing (Expand Search), melt processing (Expand Search), _ processing (Expand Search)
element » elements (Expand Search)
processing algorithm » processing algorithms (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
end processing » text processing (Expand Search), melt processing (Expand Search), _ processing (Expand Search)
element » elements (Expand Search)
-
221
BioNetApp: An interactive visual data analysis platform for molecular expressions
Published 2019“…BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.…”
-
222
Automatic keyword extraction from a real estate classifieds data set
Published 2011“…We begin with designing data cleansing algorithms to verify different attributes of the real estate classified. …”
Get full text
-
223
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. …”
-
224
-
225
A Multi-Channel Convolutional Neural Network approach to automate the citation screening process
Published 2021“…This study aims to automate the citation screening process using Deep Learning algorithms. With this, it is aimed to reduce the time and costs of the citation screening process and increase the precision and recall of the relevant primary studies. …”
-
226
-
227
Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
doctoralThesis -
228
-
229
Joint energy-distortion aware algorithms for cooperative video streaming over LTE networks
Published 2013“…In the proposed approach, mobiles are grouped into collaborative clusters using a low-complexity clustering algorithm. In each cluster, collaboration is implemented by having a cluster head send the content to other cluster members using a short-range wireless communications technology. …”
Get full text
Get full text
Get full text
article -
230
Minimizing Deadline Misses of Mobile IoT Requests in a Hybrid Fog- Cloud Computing Environment
Published 2019Get full text
doctoralThesis -
231
Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
Published 2023“…Features of transmission line maintenance were used to increase accuracy of estimation. Algorithms were tested using the test power system IEEE39. …”
Get full text
article -
232
A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
Published 2019“…To show the applicability of the proposed approach, Iran’s bitumen consumption data in the period of 1991-2006 are used as a case study. …”
Get full text
Get full text
Get full text
Get full text
article -
233
-
234
Performance evaluation of load balancing algorithms for parallel single-phase iterative PDE solvers
Published 1994“…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
Get full text
conferenceObject -
235
-
236
Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
Get full text
Get full text
Get full text
article -
237
K Nearest Neighbor OveRsampling approach: An open source python package for data augmentation
Published 2022“…This paper introduces K Nearest Neighbor OveRsampling (KNNOR) Algorithm — a novel data augmentation technique that considers the distribution of data and takes into account the k nearest neighbors while generating artificial data points. …”
-
238
-
239
KNNOR: An oversampling technique for imbalanced datasets
Published 2021“…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. However, if the training data is not balanced among different classes, the performance of ML models deteriorate heavily. …”
-
240