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implementing based » implementing bundled (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
element » elements (Expand Search)
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301
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. …”
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302
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. …”
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303
Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks
Published 2024“…The proposed algorithm unlocks scalability and system adaptability to operational variability by adopting numeric imputation and missing-data-tolerant techniques. …”
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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. …”
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A Parallel Genetic Algorithm for the Open-Shop Scheduling Problem Using Deterministic and Random Moves
Published 2016“…The method is based on a novel implementation of genetic operators that combines the use of deterministic and random moves. …”
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310
Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment
Published 2023“…First, an analytical model based on mass and energy balance and a data-driven model based on an artificial neural network is developed, and their prediction performance is compared. …”
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311
Energy-Efficient VoI-Aware UAV-Assisted Data Collection in Wireless Sensor Networks
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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms
Published 2022“…A total of eleven hundred experimental data points for nine FPs (two stratified and seven dispersed patterns) in horizontal wellbores are used to develop the MLs. …”
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314
Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems
Published 2022“…The classification performance is determined via different metrics for various GA-based ANN classifiers using data extracted from the healthy and faulty data of the GCPV system. …”
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315
Evaluation of C-arm CT metal artifact reduction algorithm during intra-aneurysmal coil embolization
Published 2016“…This analysis was carried out to assess the improvements in both brain parenchyma and device visibility with MAR algorithm. Further, ground truth reference images from phantom experiments and clinical data were used for accurate assessment. …”
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Application of updated joint detection algorithm for the analysis of drilling parameters of roof bolters in multiple joints conditions
Published 2017“…This paper reviews testing procedures, data analysis, updated algorithms used for joint detection, and discusses the latest round of testing in samples with simulated joints at various angles along the borehole.…”
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318
PILE-UP FREE PARAMETER ESTIMATION AND DIGITAL ONLINE PEAK LOCALIZATION ALGORITHMS FOR GAMMA RAY SPECTROSCOPY
Published 2020“…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. …”
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319
Detecting latent classes in tourism data through response-based unit segmentation (REBUS) in Pls-Sem
Published 2016“…This research note describes Response-Based Unit Segmentation (REBUS), a “latent class detection” technique used in partial least squares–structural equation modeling (PLS-SEM) to examine data heterogeneity. …”
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320
Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
Published 2021“…The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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