We present a comprehensive, detailed review of time-series data analysis, with emphasis on
deep time-series clustering (DTSC), and a case study in the context of movement behavior …

To achieve scientific progress in terms of building a cumulative body of knowledge, careful
attention to benchmarking is of the utmost importance, requiring that proposals of new …

Current district heating networks are undergoing a sustainable transition towards the 4 th
and 5 th generation of district heating networks, characterized by the integration of different …

With the development of data-driven models, extracting information from historical data for
better energy forecasting is critically important for energy planning and optimization in …

Global food security depends on the sustainability of irrigated agriculture. Rising
groundwater withdrawals from seasonally humid, alluvial plains across tropical Asia have …

Due to significant implications for resource and food sectors that directly influence social
well-being, commodity price comovements represent an important issue in agricultural …

Commodity price comovements are an important issue in economics given their significant
implications for food and resource sectors that directly influence social well-being. This study …

Internet of Things (IoT) time-series analysis has found numerous applications in a wide
variety of areas, ranging from health informatics to network security. Nevertheless, the …

Time series clustering is the act of grouping time series data without recourse to a label.
Algorithms that cluster time series can be classified into two groups: those that employ a time …

Abstract Machine learning (ML) is becoming increasingly crucial in many fields of
engineering but has not yet played out its full potential in bioprocess engineering. While …