International Conference on Time Series Analysis and Machine Learning (ICTSAML-27)

Conference Session Tracks

Aligned with

UN SUSTAINABLE DEVELOPMENT GOALS

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals.

SDG 4 Quality Education

SDG 8 Decent Work and Economic Growth

SDG 9 Industry, Innovation and Infrastructure

TRACK 01

Advancements in Time Series Forecasting Techniques

This track focuses on innovative methodologies for time series forecasting, emphasizing the integration of machine learn...

TRACK 02

Anomaly Detection in Temporal Data

This session will delve into the latest approaches for detecting anomalies in time series data, utilizing both supervise...

TRACK 03

Deep Learning Architectures for Sequence Modeling

This track examines the application of deep learning architectures, such as recurrent neural networks, for modeling sequ...

TRACK 04

Feature Extraction Techniques for Time Series Analysis

This session highlights advanced feature extraction methods tailored for time series analysis, focusing on enhancing pre...

TRACK 05

Temporal Data Mining and Its Engineering Applications

This track explores the intersection of temporal data mining and engineering, showcasing techniques that uncover pattern...

TRACK 06

Regression Analysis in Time Series Contexts

This session focuses on the application of regression analysis techniques to time series data, emphasizing their role in...

TRACK 07

Signal Processing Techniques for Time Series Data

This track investigates the role of signal processing in enhancing the analysis of time series data, particularly in eng...

TRACK 08

Seasonal Decomposition and Trend Analysis

This session will cover methodologies for seasonal decomposition and trend analysis in time series data, highlighting th...

TRACK 09

Event Prediction Using Machine Learning

This track focuses on the use of machine learning techniques for event prediction within time series contexts, particula...

TRACK 10

Comparative Studies of Supervised vs. Unsupervised Learning

This session aims to compare the effectiveness of supervised and unsupervised learning techniques in time series analysi...

TRACK 11

Innovations in Predictive Analytics for Engineering

This track showcases cutting-edge innovations in predictive analytics specifically tailored for engineering challenges. ...

Hybrid Event