Hybrid Conferencee

International Conference on Time Series Analysis and Stochastic Modeling (ICTSASM - 26)

13th - 14th July 2026 | Florence, Italy
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Conference Brochure
Sample Full Paper
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Conference Notifications:

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Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Florence. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the Florence event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Florence conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Florence, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Florence."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICTSASM aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Probability Theory, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

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

01
Time series forecasting techniques
02
Stochastic modeling of time-dependent data
03
Applications in financial time series analysis
04
Seasonal patterns in time series data
05
Statistical methods for time series analysis
06
ARIMA models and their applications
07
Longitudinal data analysis techniques
08
Nonlinear time series modeling approaches
09
Time series analysis in environmental studies
10
Machine learning for time series prediction
11
Causal inference in time series data
12
Time series analysis in healthcare
13
Multivariate time series modeling techniques
14
Applications in signal processing
15
Real-time analysis of streaming data
16
Time series anomaly detection methods
17
Bayesian approaches to time series
18
Time series analysis in social sciences
19
Forecasting with exogenous variables
20
Applications in supply chain management