[AISWorld] SI on "Advanced Machine Learning and Optimization Methods for Data Analytics and Security", Connection Science, Taylor & Francis

[王宇平]

Dear Staff of Connection Science,




Some authors told me that they cannot find the SI in journal home page and the corresponding link for submission. The submission button in the following link (https://shorturl.at/gqtIJ) seems not work: 

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Submission instructions:

Please read the "Guide for Authors" before submitting. All articles should be submitted online; please select SI: “Advanced Machine Learning and Optimization Methods for Data Analytics and Security” during the submission. For other details, please visit the Special Issue official website:

https://shorturl.at/gqtIJ

 

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Could you please tell me the submission link for this SI.




Thanks a lot and best regards

Yuping Wang



-----原始邮件-----
发件人:"Editorial Manager" <journaleditorialmanager at outlook.com>
发送时间:2023-11-18 07:10:07 (星期六)
收件人: "aisworld at lists.aisnet.org" <aisworld at lists.aisnet.org>
抄送:
主题: SI on "Advanced Machine Learning and Optimization Methods for Data Analytics and Security", Connection Science, Taylor & Francis



 

** Apologies if multiple copies are received **

 

Special Issue on

Advanced Machine Learning and Optimization Methods for Data Analytics and Security

Connection Science, Taylor & Francis

SCIE JCR Q1 (best quartile) | CiteScore 5.2

https://www.tandfonline.com/ccos20

 

Currently, big data handling and its security have become a new, hot research topic among academics and the industry community. The new machine learning (especially deep learning) and optimization techniques are essential tools for data analysis and ensuring data security. However, there are still numerous technical challenges and issues involving new machine learning models and optimization techniques that need to be improved and broadly explored for data analysis and security. For example, explainable deep learning models, zero-shot deep learning models, few-shot deep learning models, efficient global optimization methods for deep learning models, big data analysis and data and network security.

 

This Special Issue aims to provide the last and most innovative research on all theoretical and practical aspects of new machine learning techniques and optimization methods for data analysis, and data and network security. The topics of interest include, but are not limited to:

 

Models and methods of new deep learning

New deep learning theory

Explainable deep learning models

Machine learning algorithm in networks

Data mining for network data

New optimization methods for data analysis

Optimization models on resource allocation in wireless communications

Optimization models on task scheduling in wireless communications

New models on 5G and 6G networks

Integration of AI and wireless or next generation networks

Evolutionary algorithms for data analytical problems

Security techniques in next generation networks

Security techniques for data analytics

Security techniques and AI for data analytics

Computer network and Security

Other related topics.

 

Dates

Submission Deadline: *31 July 2024*

 

Guest Editors

Yuping Wang, Xidian University, China

Xiaozhi Gao, University of Eastern Finland, Finland

Nan Ma, Beijing University of Technology, China

Xingsi Xue, Victoria University of Wellington, New Zealand

 

Submission instructions:

Please read the "Guide for Authors" before submitting. All articles should be submitted online; please select SI: “Advanced Machine Learning and Optimization Methods for Data Analytics and Security” during the submission. For other details, please visit the Special Issue official website:

https://shorturl.at/gqtIJ