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A novel linear time corner detection algorithm
Published 2005“…We have presented a novel scheme for detecting corners of a planner object SRM05. The core of the algorithm is based upon slope analysis. …”
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Multi-Objective Co-optimization of Power and Gas under Uncertainties with P2H embedded
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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm
Published 2024“…Additionally, these data can be readily applied to compare algorithmic results referenced by (Babu, T.S. et al., 2015; PrasanthRam, J. et al., 2017) [2,3], and contribute to the development of new processes for practical applications.…”
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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
Published 2022“…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …”
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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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Estimating Construction Project Duration Using a Machine Learning Algorithm
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masterThesis -
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A Hash-Based Assessment and Recovery Algorithm for Distributed Healthcare Systems Using Blockchain Technology
Published 2020“…Numerous damage assessment and recovery algorithms have been proposed in the literature. In this work, we present a distributed algorithm that uses blockchain technology and hash tables to solve the information warfare problem in healthcare systems. …”
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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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A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems
Published 2025“…Unlike traditional attacks that use fixed or heuristic perturbation parameters, our GA-driven method dynamically evolves perturbation parameters through multi-objective fitness optimization, producing highly adaptive and effective adversarial examples. …”
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Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques
Published 2020“…This conclusion was achieved after preprocessing a number of data values from these data sets.</p><h2>Other Information</h2><p dir="ltr">Published in: Algorithms<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/a13080202" target="_blank">https://dx.doi.org/10.3390/a13080202</a></p>…”
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
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doctoralThesis -
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Web Based Online Hybrid Teaching Method of Network Music Course
Published 2022“…Based on Web data mining, an improved algorithm of hybrid hierarchical recommendation algorithm and genetic algorithm is used in the experiment, and compared with the other two algorithms in the experiment. …”
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Properties of simulated annealing and genetic algorithms for mapping data to multicomputers
Published 1997“…Some user parameters are included in the objective function and are architecture- or problem-dependent parameters. The others are used in the GA and SA algorithms. The fault tolerance capability is demonstrated by mapping data to a multicomputer with some faulty processors. …”
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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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General applicability of genetic and simulated annealing algorithms for data mapping
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Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts
Published 2022“…So far none addresses the use of Threat Intelligence (IT) data in Ensemble Learning algorithms to improve the detection process, nor does it work as a function of time, that is, taking into account what happens on the network in a limited time interval. …”
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