Call For Papers
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:
- Time series forecasting techniques
- Stochastic modeling of time-dependent data
- Applications in financial time series analysis
- Seasonal patterns in time series data
- Statistical methods for time series analysis
- ARIMA models and their applications
- Longitudinal data analysis techniques
- Nonlinear time series modeling approaches
- Time series analysis in environmental studies
- Machine learning for time series prediction
- Causal inference in time series data
- Time series analysis in healthcare
- Multivariate time series modeling techniques
- Applications in signal processing
- Real-time analysis of streaming data
- Time series anomaly detection methods
- Bayesian approaches to time series
- Time series analysis in social sciences
- Forecasting with exogenous variables
- Applications in supply chain management
Assessment
Submissions will be assessed for originality, innovation, and relevance. Accepted papers will be presented at the conference and considered for publication opportunities in reputed academic platforms.
Registration
Participants are requested to complete the registration process following acceptance of their paper. Registration ensures inclusion in the conference schedule and official records.
Publication
All accepted manuscripts will be eligible for publication consideration in conference proceedings and associated academic journals.