SMTDA2020
Date:
02.06.2020
The 6th Stochastic Modeling Techniques and Data Analysis International Conference (SMTDA2020) will be organized from 2-5 June 2020, in Barcelona, Spain, www.smtda.net.
SMTDA2020 will be hosted at the UNESCO Heritage site “Casa Convalescència”, Universitat Autonόma de Barcelona, Spain. SMTDA follows every second year for the last 12 years, the ASMDA Conferences organised from 1981 in Brussels.
Note that in SMTDA2020 we celebrate the 80th birthday of Professor Robert Elliott in honour of his contributions to Statistics, Stochastic Processes in Finance and Engineering and his support to ASMDA and SMTDA activities (see at: http://www.smtda.net/committeesplenarytalks.html ).
Important Plenary and Keynote Talks presenting the State of the Art in their fields will be addressed by:
N. Balakrishnan, McMaster University, Canada
Elena Babatsouli, University of Louisiana at Lafayette, USA
Jose H. Blanchet, Stanford University, Stanford, CA, USA
Mark Brown, Columbia University, New York, NY, USA
Ekaterina Bulinskaya, Lomonosov Moscow State University, Moscow, Russia
Lirong Cui, Beijing Institute of Technology, Beijing, P. R. China
Claude Lefèvre, Université Libre de Bruxelles, Belgium
Sally McClean, Ulster University, Coleraine, Northern Ireland
Mei-Ling Ting Lee, University of Maryland, College Park, Maryland, USA
Sheldon Mark Ross, Viterbi School of Engineering, USC, USA
Gilbert Saporta, Conservatoire National des Arts et Métiers (CNAM), Paris, France
P.-C.G. VASSILIOU, University College London, UK
David D. Yao, IE-OR Department at Columbia University, New York, NY, USA
The Stochastic Modeling Techniques and Data Analysis International Conference (SMTDA) main objective is to welcome papers, both theoretical or practical, presenting new techniques and methodologies in the broad area of stochastic modeling and data analysis. An objective is to use the methods proposed for solving real life problems by analysing the relevant data. Also, the use of recent advances in different fields will be promoted such as for example, new optimization and statistical methods, data warehouse, data mining and knowledge systems, computing-aided decision supports, neural computing and artificial intelligence.
Particular attention will be given to interesting applications in engineering, productions and services (maintenance, reliability, planning and control, quality control, finance, insurance, management and administration, inventory and logistics, marketing, environment, human resources, biotechnology, medicine, ...).
For Abstract submission and special session proposals please visit the conference website at: www.smtda.net or send email to Secretariat@smtda.net .
The Data Analysis Book from ASMDA2017 Conference in London (De Morgan House of the London Mathematical Society) is ready in 2 Volumes published by ISTE-Wiley.
An excellent introductory chapter by Gilbert Saporta honorary speech is also included. Download the books from the Wiley website at:
The SMTDA2018 Books at ISTE-Wiley are in the last stages while we collect the updated forms of the ASMDA2019 papers for the new publications.
The SMTDA2020 event will host the Demographics2020 International Workshop (The POSTER for both events is at: http://www.smtda.net/images/Poster_SMTDA2020.pdf ). The main focus is on Health State and the optimal retirement age.: More information is related to a recent work on estimating the “Health Expenditure per Age Group”. To join the ongoing international study just send me a message that you intent to contribute in a Demography publication.
CONFERENCE TOPICS
Methodological approaches
Poisson, Markov, semi-Markov processes,
Point processes,
Martingales, Stochastic calculus,
Random evolutions,
Decision and Controlled Processes,
Diffusion and Poisson approximations,
Asymptotic models and Weak Convergences,
Statistical inference for Stochastic processes ,
Hidden Markov and semi-Markov processes,
Fitting models for data,
Reliability and survival analysis,
Bayesian inference,
Functional data analysis,
Discriminant and Regression Analysis,
Mixture model and Probabilistic approach to Clustering,
Analysis of complex data (incomplete, censored, missing, spatio-temporal, imprecise, fuzzy,...),
Theories of uncertainty,
Graphical models and Bayesian networks,
Multidimensional Scaling and Multi-way Data Analysis,
Sensory Analysis,
Classification and Documentation,
Data and Text Mining,
Chaotic and Stochastic processes,
Analysis of Chaotic processes.
Special techniques and algorithms:
Neural Networks,
Genetic and Fuzzy Algorithms,
Support Vector Machine,
Monte Carlo Methods,
Chaotic Simulation
