Computational and Mathematical Methods in Information Science and Engineering

doi:10.3390/books978-3-0365-8471-3

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Computational and Mathematical Methods in Information Science and Engineering

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August 2023

402 pages

ISBN978-3-0365-8470-6 (Hardback)
ISBN978-3-0365-8471-3 (PDF)

https://doi.org/10.3390/books978-3-0365-8471-3

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This book is a reprint of the Special Issue Computational and Mathematical Methods in Information Science and Engineering that was published in

Computer Science & Mathematics

Engineering

Physical Sciences

Public Health & Healthcare

Summary

Nowadays, computational and mathematical methods provide effective tools for handling vast quantities of data and information in the fields of big data analytics, knowledge discovery and decision-making for solving complex problems in the world. The present reprint contains all of the articles accepted and published in the first edition of the Special Issue titled “Computational and Mathematical Methods in Information Science and Engineering”. The objective of this Special Issue is to provide a channel through which members of the scientific community can exchange insights regarding recent advances in the theory and application of computational and mathematical methods in information science and engineering, with the long-term goal being to solve data-handling problems in practice. We hope that the papers published in this Special Issue will be considered impactful by the international scientific community and motivate further research into computational and mathematical methods that can solve complex problems in various fields and applications.

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Keywords

multi-scale; local interaction; lightweight image reconstruction network; global fusion; green supply chain; environmental awareness; information acquisition; outsourcing; in-house; career choice; prediction; machine learning; college students; non-cooperative equilibrium; complex supply chain network; environmental policies; circular economy; structural balance; feedback mechanism; opinions polarization; reservoir characterization; productivity prediction; machine learning; knowledge interaction neural network; embedded model; egg shape equation; displacement of volume method; egg volume; classical retrial policy; queue dependent service rate; waiting time analysis; infinite orbit; private set intersection; quantum authentication; oblivious quantum key distribution; Internet of Things; multi-objective optimization; mining plan; metal mines; adaptive; hybrid mutation; multi-facility location problem; clustering algorithm; center-of-gravity method; hybrid multi-attribute; three-way group decision making; VIKOR model; grey correlation analysis; interval-valued intuitionistic fuzzy numbers; tourist arrival forecast; variational mode decomposition; empirical mode decomposition; multiscale analysis; deep learning model; convolutional neural network model; seasonal ARIMA; ARIMA; sales forecasting; demand pattern; dynamic weighting; model selection; retail; malicious network traffic; GAN; imbalanced classification; partial discharge (PD); phase-resolved PD (PRPD); rotating machine; stator coil; buffer wards; mixed-integer programming; dynamic bed allocation; patient admission control; COVID-19 pandemic; regression; data stream; non-convex loss function; noise-resilient; online-learning; ARL; control charts; COVID-19 data; deviance residuals; link functions; logistic profiling; Pearson residuals; conditional autoregressive model; Markov chain Monte Carlo; occurrence rate; spatial Poisson model; n/a