Mining and analysis of time series data (TSD) have drawn a great concern, especially in the
TSD clustering, classification, and forecast. In the industrial field, eg, the work condition …

In this paper, a novel high-accuracy and robust computing framework for time series
classification tasks is presented. The framework consists of a feature extraction module and …

Monitoring water demand is extremely helpful in the early detection of issues and
malfunctions in water distribution networks. Therefore, distinguishing abnormal water meter …

In order to improve the performance of time series similarity measure, a model combined
Siamese and Sequential Neural Network (SSNN) is proposed. The model consists of three …

Rail switches are critical infrastructure components of a railroad network, that must maintain
high-levels of reliable operation. Given the vast number and variety of switches that can exist …

Repetitive construction processes, as an essential element of construction industry, still rely
intensively on manual execution and on-site decision-making. Within the proposal for …

The objective of this study is to investigate the potential of multitemporal remote sensing
images for crop classification. Multi-temporal Landsat 8 OLI/TIRS C1 Level-1 images were …

In today's data-driven world, it is extremely important to understand the key aspects of data.
Not only this, but also the means to analyze data, extract features of data, and generate …

In der heutigen datengetriebenen Welt ist es äußerst wichtig, die Schlüsselaspekte von
Daten zu verstehen. Nicht nur das, sondern auch die Mittel zur Analyse von Daten, zur …

Traffic prediction using time series models is important for forecasting the volume and
density of traffic flow, usually for the purpose of managing vehicle movement, reducing …