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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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A Tabu Search algorithm for mapping data to multicomputers. (c1997)
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Physical optimization algorithms for mapping data to distributed-memory multiprocessors
Published 1992“…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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Parallel physical optimization algorithms for allocating data to multicomputer nodes
Published 1994“…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …”
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
Published 2022“…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …”
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…To improve the effectiveness and efficiency of the UniBFS algorithm, Redundant Features Elimination algorithm (RFE) is presented in this paper. …”
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Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm
Published 2023“…Furthermore, a route management technique is combined with Artificial Intelligence (AI) algorithm to transmit the data to appropriate central servers. …”
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Using Machine Learning Algorithms to Forecast Solar Energy Power Output
Published 2025“…The data forecasting horizon used was a 24-h window in steps of 30 min. …”
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
Published 2019“…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
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Second-order conic programming for data envelopment analysis models
Published 2022“…This paper constructs a second-order conic optimization problem unifying several DEA models. Moreover, it presents an algorithm that solves the former problem, and provides a MATLAB function associated with it. …”
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An ant colony optimization algorithm to improve software quality prediction models
Published 2011“…Method This paper presents an adaptive approach that takes already built predictive models and adapts them (one at a time) to new data. …”
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A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models
Published 2010“…In this paper, we present a genetic algorithm that adapts such models to new data. …”
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Correlation Clustering via s-Club Cluster Edge Deletion
Published 2023Subjects: “…Cluster analysis -- Data processing…”
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A data envelopment analysis model for opinion leaders’ identification in social networks
Published 2024“…Consequently, a new application of the Data Envelopment Analysis (DEA) method is presented here for OLs identification in social media. …”
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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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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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