Registration summary
ConferenceICATSFM
ModeStandard / Physical
ParticipationListener
Registration fee$175.00
Bank charges (5.8%)$10.15
Total payable$185.15
Includes all bank processing charges — the amount above is exactly what will be charged.
Benefits of Registering as Listener
Access to Conference Sessions
Networking Opportunities
Certificate of Participation
Invitation Letter Support
Conference Kit / Materials
Access to Keynote Sessions
• Conference Session Tracks •
SDG-Aligned Research Themes
ICATSFM conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.
01 Advanced Time Series Forecasting Techniques +
This track focuses on innovative methodologies for time series forecasting, emphasizing the integration of statistical models and machine learning algorithms. Participants will explore case studies and applications that demonstrate the effectiveness of these advanced techniques in various domains.
02 Statistical Modeling in Data Science +
This session will delve into the role of statistical modeling within the broader context of data science, highlighting its importance in deriving insights from complex datasets. Attendees will discuss best practices and challenges in implementing statistical models for real-world applications.
03 Predictive Analytics and Decision Making +
This track examines the intersection of predictive analytics and decision-making processes, showcasing how statistical methods can enhance forecasting accuracy. Participants will share experiences and frameworks that facilitate data-driven decision-making in diverse fields.
04 Regression Analysis and Its Applications +
Focusing on regression analysis, this session will cover various techniques and their applications in predicting outcomes and understanding relationships within data. Attendees will engage in discussions about the latest advancements and practical implementations of regression models.
05 Simulation Techniques in Statistical Analysis +
This track will explore the use of simulation techniques in statistical analysis, emphasizing their role in understanding complex systems and uncertainty. Participants will learn about various simulation methodologies and their applications in forecasting and risk assessment.
06 Probability Models in Time Series Analysis +
This session will focus on the application of probability models in time series analysis, discussing their significance in capturing underlying patterns and trends. Attendees will explore various probabilistic approaches and their implications for forecasting accuracy.
07 Machine Learning Approaches to Time Series Forecasting +
This track will investigate the application of machine learning techniques in time series forecasting, highlighting their advantages over traditional statistical methods. Participants will discuss successful case studies and the challenges of integrating machine learning into forecasting workflows.
08 Artificial Intelligence in Predictive Analytics +
This session will explore the role of artificial intelligence in enhancing predictive analytics, focusing on how AI techniques can improve forecasting models. Attendees will share insights on the integration of AI with traditional statistical methods for better predictive performance.
09 Econometric Models for Time Series Data +
This track will cover econometric models specifically designed for analyzing time series data, emphasizing their application in economic forecasting. Participants will discuss the theoretical foundations and practical implications of these models in real-world scenarios.
10 Big Data and Quantitative Methods +
This session will explore the challenges and opportunities presented by big data in the context of quantitative methods and statistical analysis. Attendees will discuss innovative approaches to harnessing big data for improved forecasting and decision-making.
11 Risk Analysis and Optimization in Forecasting +
This track will focus on the integration of risk analysis and optimization techniques in forecasting methodologies. Participants will explore how these approaches can enhance the reliability and accuracy of forecasts in uncertain environments.
