Eric Ramat

Work place: Université du Littoral Côte d’Opale, Calais, France

E-mail: ramat@lisic.univ-littoral.fr

Website:

Research Interests: Medicine & Healthcare

Biography

Eric Ramat is Full Professor in Computer Science at the LISIC Laboratory of the University of Littoral Côte d'Opale (France). He belongs to the axis Multi-modeling and evolution and he is Coordinator of team Osmose. His research topic is part of the problem of multi-modeling, modeling and simulation of complex systems applied to natural (fishing, agronomic, etc.) and artificial systems. His projects are subdivided into four main categories: Multi-agent modeling and simulation of complex phenomena (especially in natural systems); Integration by cartography and packaging of the formalities (formalities) of abstract formalism DEVS (Discrete EVent System Specification); Implementation of the V.L.E. (Virtual Laboratory Environment), the implementation of our tools and approaches for multi-modeling; Application to marine ecosystems, maritime economy, agronomic systems, etc.

Author Articles
Meta-Population Modelling and Simulation of the Dynamic of Malaria Transmission with Influence of Climatic Factors

By Justin-Herve NOUBISSI Jean Claude Kamgang Eric Ramat Januarius Asongu Christophe Cambier

DOI: https://doi.org/10.5815/ijitcs.2017.07.01, Pub. Date: 8 Jul. 2017

We model the dynamic of malaria transmission taking into account climatic factors and the migration between Douala and Yaounde´, Yaounde´ and Ngaounde´re´, three cities of Cameroon country. We show how variations of climatic factors such as temperature and relative humidity affect the malaria spread. We propose a meta-population model of the dynamic transmission of malaria that evolves in space and time and that takes into account temperature and relative humidity and the migration between Douala and Yaounde´, Yaounde´ and Ngaounde´re´. More, we integrate the variation of environmental factors as events also called mathematical impulsion that can disrupt the model evolution at any time. Our modelling has been done using the Discrete EVents System Specification (DEVS) formalism. Our implementation has been done on Virtual Laboratory Environment (VLE) that uses DEVS formalism and abstract simulators for coupling models by integrating the concept of DEVS.

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