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International Conference on Stochastic Modeling in Environmental and Biological Systems - (ICSMEBS-27)

27th - 28th February 2027 , Erdenet - Mongolia

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Call For Papers

The (ICSMEBS-27) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Probability Theory, Statistics are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Stochastic modeling in ecological systems
  • Applications of stochastic modeling in biology
  • Stochastic processes in environmental risk assessment
  • Modeling biological systems with stochastic methods
  • Stochastic modeling in climate change studies
  • Applications of stochastic modeling in agriculture
  • Stochastic processes in wildlife management
  • Stochastic modeling for public health
  • Applications of stochastic modeling in conservation
  • Stochastic modeling in epidemiological studies
  • Stochastic processes in environmental policy
  • Modeling environmental systems with stochastic methods
  • Stochastic modeling in water resource management
  • Applications of stochastic modeling in forestry
  • Stochastic processes in urban ecology
  • Stochastic modeling in fisheries management
  • Stochastic approaches to biodiversity assessment
  • Applications of stochastic modeling in pollution control
  • Stochastic modeling in renewable energy systems
  • Stochastic processes in land use planning

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.