The 2nd Int'l Conference on Statistics, Mathematical Modelling and Analysis (SMMA 2019) will be held from July 19-21, 2019 in Guilin, China. SMMA 2019 will cover issues on Statistics, Mathematical Modelling and Analysis. It dedicates to creating a stage for exchanging the latest research results and sharing the advanced research methods.

Call For Papers

The 2nd Int'l Conference on Statistics, Mathematical Modelling and Analysis (SMMA 2019)

Conference Date: July 19-21, 2019Conference Venue: Guilin, ChinaWebsite: Registration System: 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 related to Applied Mathematics and PhysicsIndex: 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: intelconf@163.comTel: +86 132 6470 2250QQ: 3025797047WeChat: 3025797047 

Conference Topics

Topics: The conference is soliciting state-of-the-art research papers in the following areas of interest: Actuarial scienceApplied data mining and statistical learningApplied SimulationApplied statisticsApplied time series analysisBiometrics and applied statisticsBiostatistics and bioinformaticsData modeling and analysisDesign of simulation experimentsEconometricsFinancial mathematicsGeostatisticsImage, speech and video processing and analysisLinear algebra and programming modelsMathematical modellingMetamodelling and regressionModel verification and validationModeling and simulationModeling simulation inputsNumerical analysisPattern recognition and analysisRandom processesReal analysis and statisticsSampling techniquesSatisfiability modulo theoriesSensitivity analysisSingular perturbation theorySmoothing and statistical graphicsSocial science methodologyStatistical analysis system programmingStatistical applicationsStatistical geneticsStatistics and mathematics educationStatistics for environmentsStochastic modelling