Hybrid Conference (In Person / Virtual)

International Conference on Time Series Analysis and Probabilistic Forecasting (ICTSAPF - 27)
18th - 19th February 2027 , Munich, Germany
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Conference Notifications:

"Be sure to check this section regularly for all IIRD Global Conference updates. We’ll keep you informed about deadlines, event details, and more important notifications."

  • Abstract Submissions Open:
    "We are now accepting abstract submissions for the IIRD Global Conference in Munich. Submit your abstract by today to be part of this exciting international event." Call for Abstracts – Submit Now!
  • Paper Submission Guidelines:
    "Please ensure your paper follows the submission guidelines for smooth processing. Visit our paper submission page for more details."
  • Peer Review Process:
    "The peer review process will begin soon. Authors will receive valuable feedback that will help enhance their presentations for the Munich conference."
  • Networking with Global Experts:
    "Join global experts at our conference in Munich and engage in meaningful conversations. Build relationships that last." Register now to join!
  • Best Paper Presentation Award:
    Dr. Shatha Hawarna from Hamdan Bin Mohammed Smart University received the Best Paper Presentation Award at (ICBAI-25) in Bangkok, Thailand.
  • SDG-Inspired Conference Focus:
    "The conference will explore themes related to sustainability and inclusive development, with an emphasis on research that contributes to global well-being."

Call For Papers

The ICTSAPF provides a supportive platform for both experienced researchers and early-career academicians to present their work and gain recognition.

The conference covers diverse topics such as Probability Theory, Statistics, encouraging participation from emerging researchers and fostering academic growth.

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

01
Time series modeling techniques
02
Probabilistic forecasting methods
03
Statistical analysis of time series
04
Seasonal decomposition in forecasting
05
Machine learning for time series
06
Bayesian approaches to forecasting
07
Temporal data mining techniques
08
Longitudinal data analysis methods
09
Autoregressive integrated moving average
10
Forecasting with neural networks
11
Causal inference in time series
12
Real-time forecasting applications
13
Time series anomaly detection
14
Multivariate time series analysis
15
Time series in economics
16
Dynamic systems and forecasting
17
Forecasting in climate science
18
Time series and big data
19
Statistical software for time series
20
Emerging trends in time series analysis

Assessment

Submissions will be reviewed to ensure quality and relevance, with a focus on encouraging emerging research contributions. Accepted papers will be presented and considered for publication opportunities.

Registration

Early-career researchers are encouraged to register and present their work, gaining valuable feedback and academic exposure.

Publication

The conference provides opportunities for emerging researchers to publish their work in recognized platforms.

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