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processing algorithm » processing algorithms (Expand Search)
modelling algorithm » scheduling algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems
Published 2024“…Feature selection (FS) is the activity of defining the most contributing feature subset among all used features to improve the superiority of datasets with a large number of dimensions by selecting significant features and eliminating redundant and irrelevant ones. Therefore, this process can be seen as an optimization process. The primary goals of feature selection are to decrease the number of dimensions and enhance classification accuracy in many domains, such as text classification, large-scale data analysis, and pattern recognition. …”
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443
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A modified coronavirus herd immunity optimizer for capacitated vehicle routing problem
Published 2021“…To evaluate the modified CHIO, twosets of data sets are used: the first data set has ten Synthetic CVRP models while the second is an ABEFMPdata set which has 27 instances with different models. …”
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445
Cross entropy error function in neural networks
Published 2002“…To forecast gasoline consumption (GC), the ANN uses previous GC data and its determinants in a training data set. …”
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446
Corrosion Monitoring Technologies for Reinforced Concrete Structures: A Review
Published 2023“…New technology, algorithms, data processing, and AI are new approaches to improving corrosion monitoring processes. …”
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447
An Infrastructure-Assisted Workload Scheduling for Computational Resources Exploitation in the Fog-Enabled Vehicular Network
Published 2020“…A Dantzig–Wolfe decomposition algorithm is proposed which yields to a master program solvable by the Barrier algorithm and subproblems solve...…”
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448
Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier
Published 2021“…<div><p>Machine learning (ML)-based prediction is considered an important technique for improving decision making during the planning process. Modern ML models are used for prediction, prioritization, and decision making. …”
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449
Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context
Published 0024“…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …”
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450
Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization
Published 2023“…Typically, they can (i) ease the training process, (ii) improve the generalizability of ML and DL models, and (iii) overcome data scarcity problems by transferring knowledge from one domain to another or from one task to another. …”
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451
Exploring Digital Competitiveness through Bayesian Belief Networks
Published 2025“…The methodology involves constructing BBN models using data from the IMD Digital Competitiveness Ranking 2023 for 64 countries. …”
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452
Reconstruction and simulation of neocortical microcircuitry
Published 2015“…The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse experimental data. …”
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453
Predicting COVID-19 cases using bidirectional LSTM on multivariate time series
Published 2022“…Unlike other forecasting techniques, our proposed approach first groups the countries having similar demographic and socioeconomic aspects and health sector indicators using K-means clustering algorithm. The cumulative case data of the clustered countries enriched with data related to the lockdown measures are fed to the bidirectional LSTM to train the forecasting model. …”
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CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…Among the task-specific models, the SVM trained on word data achieved the highest accuracy of 91.7%. …”
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Anonymizing multimedia documents
Published 2016“…We provide a sanitizing MD∗-algorithm to enforce de-linkability along with a utility function to evaluate the utility of multimedia documents that is preserved after the sanitizing process. …”
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456
Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review
Published 2022“…WDs coupled with artificial intelligence (AI) algorithms show promise to help understand and conclude meaningful information from the gathered data and provide advanced and clinically meaningful analytics.…”
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Active distribution network type identification method of high proportion new energy power system based on source-load matching
Published 2023“…Firstly, the typical daily output scenarios of DG are extracted by clustering method, and the generalized load curve model is solved by the optimization algorithm to obtain the source load operation data; Secondly, calculate the source-load matching indicators (including matching performance, matching degree, and matching rate) according to the source load data of each region, and identify the distribution network type according to the range of the index values; Finally, several indicators are introduced to quantify the characteristics of different types of distribution networks. …”
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459
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…Among the task-specific models, the SVM trained on word data achieved the highest accuracy of 91.7%. …”
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On the complexity of multi-parameterized cluster editing
Published 2017“…In other words, Cluster Editing can be solved efficiently when the number of false positives/negatives per single data element is expected to be small compared to the minimum cluster size. …”
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