Other
Conference Title | (SMMA 2020) The 3rd Int'l Conference on Statistics, Mathematical Modelling and Analysis |
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Conference Dates | May 29-31 , 2020 |
Submission Deadline | 2019-12-09 |
Indexes | CNKI, Google Scholar |
Official Web Site | https://www.maymeeting.org/conference/SMMA2020/ |
Venue | Ramada Xiamen Hotel |
Location | Xiamen , China |
Description | Int'l Conference on Statistics, Mathematical Modelling and Analysis (SMMA 2020) Conference Date: May 29-31, 2020 Conference Venue: Xiamen, China Website: http://www.maymeeting.org/conference/SMMA2020/ Online Registration System: http://www.maymeeting.org/RegistrationSubmission/default.aspx?ConferenceID=1229 Email: wsconf5@163.com Int'l Conference on Statistics, Mathematical Modelling and Analysis (SMMA 2020) will be held from May 29-31, 2020 in Xiamen, China. SMMA 2020 will cover issues on Applied statistics, Data modeling and analysis, Design of simulation experiments, Statistical analysis system programming, Statistical applications, Statistical genetics, Statistics and mathematics education, etc. It dedicates to creating a stage for exchanging the latest research results and sharing the advanced research methods. If you wish to serve the conference as an invited speaker, please send email to us with your CV. We'll contact with you asap. Publication and Presentation Publication: Open Access Journal,please contact us for detailed information Index: CNKI and Google Scholar Note: If you want to present your research results but do NOT wish to publish a paper, you may simply submit an Abstract to our Registration System. Contact Us Email: wsconf5@163.com Tel: +86 132 6470 2250 QQ: 1349406763 WeChat: 3025797047 Attendance Methods 1.Submit full paper (Regular Attendance+Paper Publication+Presentation) You are welcome to submit full paper, all the accepted papers will be published by Open access journal. 2. Submit abstract (Regular Attendance+Abstract+Presentation) 3. Regular Attendance (No Submission Required) Conference Topics Actuarial science Applied data mining and statistical learning Applied Simulation Applied statistics Applied time series analysis Biometrics and applied statistics Biostatistics and bioinformatics Data modeling and analysis Design of simulation experiments Econometrics Financial mathematics Geostatistics Image, speech and video processing and analysis Linear algebra and programming models Mathematical modelling Metamodelling and regression Model verification and validation Modeling and simulation Modeling simulation inputs Numerical analysis Pattern recognition and analysis Random processes Real analysis and statistics Sampling techniques Satisfiability modulo theories Sensitivity analysis Singular perturbation theory Smoothing and statistical graphics Social science methodology Statistical analysis system programming Statistical applications Statistical genetics Statistics and mathematics education Statistics for environments Stochastic modelling |
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