Publications: time series

Evolutionary multivariate time series prediction

Multivariate time series (MTS) prediction plays a significant role in many practical data mining applications, such as finance, energy supply, and medical care domains. Over the years, various predi

Unsupervised online change point detection in high-dimensional time series

A critical problem in time series analysis is change point detection, which identifies the times when the underlying distribution of a time series abruptly changes. However, several shortcomings l

A Scalable Room Occupancy Prediction with Transferable Time SeriesDecomposition of CO\(_\mbox2\) Sensor Data

Human occupancy counting is crucial for both space utilisation and building energy optimisation. In the current article, we present a semi-supervised domain adaptation method for carbon dioxide - H

SD-HOC: Seasonal Decomposition Algorithm for Mining Lagged Time Series

Mining time series data is a difficult process due to the lag factor and different time of data arrival. In this paper, we present Seasonal Decomposition for Human Occupancy Counting (SD-HOC), a c

A Scalable Room Occupancy Prediction with Transferable Time Series Decomposition of CO 2 Sensor Data

Human occupancy counting is crucial for both space utilisation and building energy optimisation. In the current article, we present a semi-supervised domain adaptation method for carbon dioxide - H

Unsupervised online change point detection in high-dimensional timeseries

A critical problem in time series analysis is change point detection, which identifies the times when the underlying distribution of a time series abruptly changes. However, several shortcomings l

Evolutionary Ensemble Learning for Multivariate Time Series Prediction

Multivariate time series (MTS) prediction plays a key role in many fields such as finance, energy and transport, where each individual time series corresponds to the data collected from a certain

A scalable room occupancy prediction with transferable time series decomposition of CO2 sensor data

Human occupancy counting is crucial for both space utilisation and building energy optimisation. In the current article, we present a semi-supervised domain adaptation method for carbon dioxide - H

© 2021 Flora Salim - CRUISE Research Group.