With the increasing role of ICT in enabling and supporting smart cities, the demand for big
data analytics solutions is increasing. Various artificial intelligence, data mining, machine …

Climate science as a data-intensive subject has overwhelmingly affected by the era of big
data and relevant technological revolutions. The big successes of big data analytics in …

This paper presents ensemble models for forecasting big data time series. An ensemble
composed of three methods (decision tree, gradient boosted trees and random forest) is …

Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay
between space and time. Several available surveys capture STDM advances and report a …

Climate science has become more ambitious in recent years as global awareness about the
environment has grown. To better understand climate, historical climate (eg archived …

Big Data have emerged and become the norm in the past decade with its well-known 4V
challenges and now adds value (a 5th V) for scientific research and the development of new …

The randomness of the wind speed leads to the intermittency of wind power, which is a
challenge to realize wind power energy as reliable and renewable power. The prediction of …

This paper introduces the open-source Beast system for scalable exploratory data science
on big spatio-temporal data. Beast is based on well-established research and has been …

Geospatial big data plays a major role in the era of big data, as most data today are
inherently spatial, collected with ubiquitous location-aware sensors such as mobile apps …

Big data analytics (BDA) is regarded as an advanced tool for achieving sustainable
development as part of the grand challenges (GCs). However, it is not clear how BDA can be …