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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT
Published 2023“…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…To achieve this goal, supervised machine learning was employed to train models on graphs with labeled data points, where each graph contains a set of points and a label indicating the centroid determined by K-means. …”
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masterThesis -
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…However, high dimensional data often contains irrelevant features, outliers, and noise, which can negatively impact model performance and consume computational resources. …”
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Playout scheduling technique based on normalized least mean square (NLMS) algorithm
Published 2006Get full text
masterThesis -
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Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study
Published 2022“…This methodology includes a variance-based sensitivity analysis to determine building parameters that significantly influence indoor air temperatures, the Multi-Objective Genetic Algorithm to calibrate different rooms simultaneously based on the significant param eters identified by the sensitivity analysis, and new evaluation criteria to achieve a high-accuracy calibrated model. …”
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Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain
Published 2017“…The VIIRS Environmental Data Record data (VIIRS_EDR) is produced operationally by NOAA, and is based on the MODIS atmospheric correction algorithm. …”
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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Scatter search for protein structure prediction. (c2008)
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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
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Development of an Optimization Algorithm for Internet Data Traffic
Published 2020“…In this paper, an optimization algorithm is proposed to reduce net data traffic, which works at Internet layer in the TCP/IP reference model. …”
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Efficient Approximate Conformance Checking Using Trie Data Structures
Published 2021Subjects: “…Estimation error,Runtime,Computational modeling,Data structures,Approximation algorithms,Encoding,Computational efficiency…”
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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm
Published 2024“…This article outlines the input data and partial shading conditions employed in the replication model of Sequential Monte Carlo (SMC)-based tracking techniques for photovoltaic (PV) systems. …”
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A Tabu Search algorithm for mapping data to multicomputers. (c1997)
Published 1997Get full text
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masterThesis -
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Allocating data to distributed-memory multiprocessors by genetic algorithms
Published 2016“…We present three genetic algorithms (GAs) for allocating irregular data sets to multiprocessors. …”
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A neural networks algorithm for data path synthesis
Published 2003“…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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Variable Selection in Data Analysis: A Synthetic Data Toolkit
Published 2024“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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