In recent years, with the rapid development of distributed photovoltaic systems (DPVS), the
shortage of data monitoring devices and the difficulty of comprehensive coverage of …

Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …

Time-Series clustering is one of the important concepts of data mining that is used to gain
insight into the mechanism that generate the time-series and predicting the future values of …

Coupled behaviors refer to the activities of one to many actors who are associated with each
other in terms of certain relationships. With increasing network and community-based events …

An automatic stock market categorization system would be invaluable to individual investors
and financial experts, providing them with the opportunity to predict the stock price changes …

Nowadays, great quantities of data are produced by a large and diverse family of sensors
(eg, remote sensors, biochemical sensors, wearable devices), which typically measure …

Time series is a very popular type of data which exists in many domains. Clustering time
series data has a wide range of applications and has attracted researchers from a wide …

The existing body of research on dynamic customer segmentation has primarily focused on
segment-level customer purchasing behavior (CPB) analysis to tailor marketing strategies …

Real-time anomaly detection at metro stations is a very important task with considerable
implications for massive passenger flow organization and train timetable rescheduling. State …

Recently there has been an increase in the studies on time-series data mining specifically
time-series clustering due to the vast existence of time-series in various domains. The large …