The use of renewable energy resources, especially wind power, is receiving strong attention
from governments and private institutions, since it is considered one of the best and most …

Artificial intelligence (AI) techniques have substantially changed the research paradigm in
the field of air quality forecasting due to their powerful performance. Considering the …

High-frequency monitoring of agrometeorological parameters is quintessential in the domain
of Precision Agriculture (PA), where timeliness of collected observations and the ability to …

In this paper, we propose a machine learning approach for forecasting hierarchical time
series. When dealing with hierarchical time series, apart from generating accurate forecasts …

Sustainable energy is the new normal towards saving the environment, thus resources
generating sustainable green energy have gained global attention. Out of all the …

Data quality significantly impacts the results of data analytics. Researchers have proposed
machine learning based anomaly detection techniques to identify incorrect data. Existing …

With major ramifications for agriculture, water resource management, and disaster planning,
rainfall prediction is an essential component of weather forecasting. The use of big data …

Time series appear in many scientific fields and are an important type of data. The use of
time series analysis techniques is an essential means of discovering the knowledge hidden …

To predict the future behavior of a system, we can exploit the information collected in the
past, trying to identify recurring structures in what happened to predict what could happen, if …

Purpose This paper aims to explore the current state of research on supply chain flexibility
(SCF) and mass personalization (MP) to identify the literature findings to date, research gaps …