Computational and Mathematical Methods in Information Science and Engineering

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 accep...

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Other Authors: Zhang, Wen (Editor), Xu, Xiaofeng (Editor), Wu, Jun (Editor), He, Kaijian (Editor)
Format: Electronic Book Chapter
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:
GAN
ARL
n/a
Online Access:DOAB: download the publication
DOAB: description of the publication
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520 |a 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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650 7 |a Mathematics & science  |2 bicssc 
653 |a multi-scale 
653 |a local interaction 
653 |a lightweight image reconstruction network 
653 |a global fusion 
653 |a green supply chain 
653 |a environmental awareness 
653 |a information acquisition 
653 |a outsourcing 
653 |a in-house 
653 |a career choice 
653 |a prediction 
653 |a machine learning 
653 |a college students 
653 |a non-cooperative equilibrium 
653 |a complex supply chain network 
653 |a environmental policies 
653 |a circular economy 
653 |a structural balance 
653 |a feedback mechanism 
653 |a opinions polarization 
653 |a reservoir characterization 
653 |a productivity prediction 
653 |a knowledge interaction neural network 
653 |a embedded model 
653 |a egg shape equation 
653 |a displacement of volume method 
653 |a egg volume 
653 |a classical retrial policy 
653 |a queue dependent service rate 
653 |a waiting time analysis 
653 |a infinite orbit 
653 |a private set intersection 
653 |a quantum authentication 
653 |a oblivious quantum key distribution 
653 |a Internet of Things 
653 |a multi-objective optimization 
653 |a mining plan 
653 |a metal mines 
653 |a adaptive 
653 |a hybrid mutation 
653 |a multi-facility location problem 
653 |a clustering algorithm 
653 |a center-of-gravity method 
653 |a hybrid multi-attribute 
653 |a three-way group decision making 
653 |a VIKOR model 
653 |a grey correlation analysis 
653 |a interval-valued intuitionistic fuzzy numbers 
653 |a tourist arrival forecast 
653 |a variational mode decomposition 
653 |a empirical mode decomposition 
653 |a multiscale analysis 
653 |a deep learning model 
653 |a convolutional neural network model 
653 |a seasonal ARIMA 
653 |a ARIMA 
653 |a sales forecasting 
653 |a demand pattern 
653 |a dynamic weighting 
653 |a model selection 
653 |a retail 
653 |a malicious network traffic 
653 |a GAN 
653 |a imbalanced classification 
653 |a partial discharge (PD) 
653 |a phase-resolved PD (PRPD) 
653 |a rotating machine 
653 |a stator coil 
653 |a buffer wards 
653 |a mixed-integer programming 
653 |a dynamic bed allocation 
653 |a patient admission control 
653 |a COVID-19 pandemic 
653 |a regression 
653 |a data stream 
653 |a non-convex loss function 
653 |a noise-resilient 
653 |a online-learning 
653 |a ARL 
653 |a control charts 
653 |a COVID-19 data 
653 |a deviance residuals 
653 |a link functions 
653 |a logistic profiling 
653 |a Pearson residuals 
653 |a conditional autoregressive model 
653 |a Markov chain Monte Carlo 
653 |a occurrence rate 
653 |a spatial Poisson model 
653 |a n/a 
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