بدائل البحث:
using algorithm » cosine algorithm (توسيع البحث)
data algorithm » jaya algorithm (توسيع البحث), deer algorithm (توسيع البحث)
developing ii » developing a (توسيع البحث), developing _ (توسيع البحث)
ii algorithm » rd algorithm (توسيع البحث), _ algorithms (توسيع البحث)
element » elements (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
data algorithm » jaya algorithm (توسيع البحث), deer algorithm (توسيع البحث)
developing ii » developing a (توسيع البحث), developing _ (توسيع البحث)
ii algorithm » rd algorithm (توسيع البحث), _ algorithms (توسيع البحث)
element » elements (توسيع البحث)
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261
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262
UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
منشور في 2024"…To overcome these challenges, a new FS algorithm named Uniform-solution-driven Binary Feature Selection (UniBFS) has been developed in this study. …"
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263
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264
SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data
منشور في 2018"…Various weighting functions and a parallelized search algorithm have been developed for that purpose and are presented here. …"
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article -
265
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266
Joint energy-distortion aware algorithms for cooperative video streaming over LTE networks
منشور في 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. …"
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article -
267
Minimizing Deadline Misses of Mobile IoT Requests in a Hybrid Fog- Cloud Computing Environment
منشور في 2019احصل على النص الكامل
doctoralThesis -
268
Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
منشور في 2023"…Features of transmission line maintenance were used to increase accuracy of estimation. Algorithms were tested using the test power system IEEE39. …"
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article -
269
A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
منشور في 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. …"
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article -
270
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271
Performance evaluation of load balancing algorithms for parallel single-phase iterative PDE solvers
منشور في 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. …"
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conferenceObject -
272
Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
منشور في 2020"…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …"
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احصل على النص الكامل
article -
273
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274
Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE
منشور في 2023"…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …"
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275
Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE
منشور في 2023"…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …"
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article -
276
K Nearest Neighbor OveRsampling approach: An open source python package for data augmentation
منشور في 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. …"
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277
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278
KNNOR: An oversampling technique for imbalanced datasets
منشور في 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. …"
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279
Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment
منشور في 2023"…A robust model predictive control strategy, based on the minimax objective function and particle swarm optimisation algorithm, is developed to handle the uncertainties in the system. …"
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280