Measured and simulated data sources from the built environment are increasing rapidly. It is
becoming normal to analyze data from hundreds, or even thousands of buildings at once …

With the rapid development of the Internet of Things (IoT), Big Data technologies have
emerged as a critical data analytics tool to bring the knowledge within IoT infrastructures to …

A case study of residential electricity consumption patterns mining and abnormal user
identification using hierarchical clustering is presented in this paper. First, based on a brief …

The recent increasing spread of Advanced Metering Infrastructure (AMI) has enabled the
collection of a huge amount of building related-data which can be exploited by both energy …

With the increasing penetration of information and communication technologies (ICTs) in
energy systems, traditional energy systems are being digitized. Advanced analysis of the …

This study focuses on the inference of characteristic data from a data set of 507 non-
residential buildings. A two-step framework is presented that extracts statistical, model …

In recent years, a large number of building energy consumption prediction models, with
various intended uses, have been proposed. The majority of these models have either taken …

Occupants are integral elements of a building ecosystem and their behavior can have a
substantial impact on energy consumption in buildings. A wide range of energy feedback …

This paper addresses the problem of reducing the number of values required to characterize
an electricity demand profile, which is usually known as its dimensionality. This reduction …

Due to high implementation rates of smart meter systems, considerable amount of research
is placed in machine learning tools for data handling and information retrieval. A key tool in …