International Conference on Time Series Analysis and Probabilistic Forecasting ICTSAPF

Call For Papers

The ICTSAPF bridges the gap between academia and industry by promoting research with practical applications. It provides a platform for professionals and researchers to share insights that drive real-world impact.

The conference focuses on Probability Theory, Statistics , encouraging applied research, case studies, and industry-driven innovations.

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

Submissions will be evaluated based on applicability, innovation, and research contribution. Accepted papers will be presented and considered for publication in reputed journals and conference proceedings.

Registration

Complete your registration to participate in discussions that bridge academia and industry, and gain exposure to practical insights.

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Publication

Selected papers will be considered for publication platforms that support academic and industry collaboration.

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Hybrid Event