2020 International Conference on Modeling, Big Data Analytics and Simulation (MBDAS2020) will be held in Xiamen, China during December 20-21, 2020 as one of the most important leading annual conference. This conference will promote the effective exchange of academic research in Modeling, Big Data Analytics, Simulation and more high frequency hot spot research fields.
MBDAS2020 sincerely welcome interested researchers and professors to understand the frontier research trends and share latest research results, summarize current work and inspire scientific research ideas, broaden horizons and cultivate scientific research interest. The conference can also be described as a remarkable opportunity for the academic and industrial communities to discuss recent developments in the fields of Modeling, Big Data Analytics and Simulation.
Sincerely looking forward for your paper submissions and invite you to participate in MBDAS2020 Conference in Xiamen, China during December 20-21, 2020! December 20-21, 2020
All papers accepted by 2020 International Conference on Modeling, Big Data Analytics and Simulation (MBDAS2020) will be published by the Journal of Physics: Conference Series https://iopscience.iop.org/journal/1742-6596, and the proceedings will be submitted by the Journal of Physics: Conference Series for EI Compendex, CPCI-S (ISTP), Scopus, Inspec and CNKI indexing. Journal of Physics: Conference Series is an open-access proceedings journal, and MBDAS2020 papers will be online available in full text via the press platform.
|Journal of Physics: Conference Series
Online ISSN: 1742-6596
Print ISSN: 1742-6588
Index by: EI Compendex, CPCI-S(ISTP), Scopus, Inspec, CNKI, etc
|Journal of Physics: Conference Series EI 最新检索截图|
MBDAS2020收录的文章将由英国皇家物理学会(IOP Publishing)旗下的Journal of Physics: Conference Series期刊出版，提交的检索机构为：EI Compendex、CPCI-S(即ISTP)、CNKI、Scopus、Inspec等。目前，Journal of Physics: Conference Series提交EI数据库检索情况稳定，作者可登陆EI数据库自行查看近期检索情况。
All submissions should be original, professional and have not been published elsewhere. Paper length should exceed 4 pages followed and it need be formatted strictly according to the Template.
Submissions must be original, unpublished work, and not have been submitted to another conference or journal for publication. All submission will be peer-reviewed roughly by at least 2-3 experts.
Authors are invited to submit English papers. Please confirm your papers with clear argumentation, close core, sufficient theoretical analysis, proper language and standard grammar in English.
Submission of a paper implies that should the paper be accepted for formal publication, at least one of the authors will register and present the paper in the conference. Plagiarism in any form is not allowed.
2020 International Conference on Modeling, Big Data Analytics and Simulation (MBDAS2020) uses the iThenticate software to detect instances of overlapping and similar text in submitted manuscripts. iThenticate software checks content against a database of periodicals, the Internet, and a comprehensive article database.
On behalf of MBDAS2020 organizing committee, we sincerely invite you to submit academic papers, share valuable experiences with colleagues and participate with wonderful presentations.
1. Please format your paper strictly according to Template and fill in Submission form. Submission subject as “submission+name+tel.”
2. Each submission should be at least 4 pages. Shorter papers should not be included in the conference proceedings.
3. All papers should be with clear argumentation, sufficient theoretical analysis, proper language and standard English grammar.
4. Please submit your paper and Submission Form to email@example.com before submission deadline: December 2, 2020.
2020 International Conference on Modeling, Big Data Analytics and Simulation (MBDAS2020) will be held on December 20-21, 2020, Xiamen, China as a platform for experienced and practical researchers from academia and industry working in the related fields to share and discuss the most advanced researches and future academic directions.
MBDAS2020 calling for high quality papers of Modeling, Big Data Analytics and Simulation including, but not limited to:
|Many thanks to Prof. Abdollah Esmaeili for the Keynote Speech titled Using Modeling Technology to Optimize Production of an Oil Field!|
|Welcome Prof. Abdollah Esmaeili from Al-Farabi Kazakh National University, Kazakhstan to join MBDAS2020 and make the Keynote Speech!|
|MBDAS2020 has entered the official list of Conference Partner!|
|If you have any questions or want know more details, welcome enter into website or contact us timely.|
|The conference schedule has been updated on the conference homepage, please check it on CONFERENCE SCHEDULE.|
|If you’re interested in academic research in Modeling, Big Data Analytics and Simulation and joining in MBDAS2020 as Reviewer, General Chair, Editor, please send your latest CV and photo to firstname.lastname@example.org now.|
|MBDAS2020 has been included by (Check)|
|MBDAS2020 has been included by WikiCFP (Check)|
|Welcome to submit original research papers mainly covering Modeling, Big Data Analytics and Simulation and more related topics to email@example.com before deadline on December 2, 2020.|
As Author: If you want to share you latest research results by giving oral/poster presentation and publish papers on MBDAS2020, please submit your full paper to firstname.lastname@example.org. You will also have a chance to hear about ideas from people in related fields.
As Reviewer: To ensure the fairness and guarantee the quality of MBDAS2020, we cordially invite experts and scholars in the fields of Modeling, Big Data Analytics and Simulation to join us as a reviewer. If you are interested, please send your CV and photo to email@example.com.
As Listener: You are also warmly welcomed to take part in MBDAS2020 as a listener even though you have no paper to submit. In the fields of Modeling, Big Data Analytics and Simulation, MBDAS2020 is the better platform and uncommon opportunity to meet experts and researchers, don’t hesitate to send your request to firstname.lastname@example.org.