Call For Papers
The ICTSAML 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 Machine Learning, 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 with machine learning
- Anomaly detection in time series data
- Applications of time series analysis
- Feature extraction techniques for time series
- Real-time time series processing methods
- Seasonal decomposition of time series
- Machine learning for financial time series
- Time series data visualization techniques
- Predictive modeling for time series data
- Challenges in time series forecasting
- Time series classification methods
- Machine learning for sensor time series
- Temporal data mining techniques
- Time series analysis in healthcare
- Machine learning for climate data
- Data preprocessing for time series analysis
- Future trends in time series research
- Machine learning for energy time series
- Time series data integration methods
- Collaborative time series analysis
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.