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data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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Practical Multiple Node Failure Recovery in Distributed Storage Systems
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Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu
Published 2024Subjects: -
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Severity-Based Prioritized Processing of Packets with Application in VANETs
Published 2019“…In this study, we propose a generic prioritization and resource management algorithm that can be used to prioritize processing of received packets in vehicular networks. …”
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Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting
Published 2019“…The learned factors, with a graph-based temporal dependency, are then used in an autoregressive algorithm to predict the future state of the road network with a large horizon. …”
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Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices
Published 2025“…Drawing on data from the Smart Cities Index (SCI) and other economic and sustainability competitiveness metrics, the study uses various <u>ML algorithms</u> to categorize cities into <u>performance classes</u>, ranging from high-achieving Class 1 to emerging Class 3 cities. …”
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Enhanced climate change resilience on wheat anther morphology using optimized deep learning techniques
Published 2024“…Various Deep Learning algorithms, including Convolution Neural Network (CNN), LeNet, and Inception-V3 are implemented to classify the records and extract various patterns. …”
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Bee Colony Algorithm for Proctors Assignment.
Published 2015“…The Bee Colony algorithm is a recent population-based search algorithm that mimics the natural behavior of swarms of honey bees during the process of collecting food. …”
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Unsupervised outlier detection in multidimensional data
Published 2022“…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …”
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R-CONV++: uncovering privacy vulnerabilities through analytical gradient inversion attacks
Published 2025“…<p dir="ltr">Federated learning has emerged as a prominent privacy-preserving technique for leveraging large-scale distributed datasets by sharing gradients instead of raw data. …”
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