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International Conference on Time Series Analysis and Probabilistic Forecasting - (ICTSAPF-27)

26th - 27th June 2027 , Beijing - China

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Call For Papers

The (ICTSAPF-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:

  • Time series modeling techniques
  • Probabilistic forecasting methods
  • Statistical analysis of time series
  • Seasonal decomposition in forecasting
  • Machine learning for time series
  • Bayesian approaches to forecasting
  • Temporal data mining techniques
  • Longitudinal data analysis methods
  • Autoregressive integrated moving average
  • Forecasting with neural networks
  • Causal inference in time series
  • Real-time forecasting applications
  • Time series anomaly detection
  • Multivariate time series analysis
  • Time series in economics
  • Dynamic systems and forecasting
  • Forecasting in climate science
  • Time series and big data
  • Statistical software for time series
  • Emerging trends in time series analysis

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.

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