This website uses cookies.
We use cookies to improve your online experience. By continuing to use our website we assume you agree to the placement of these cookies.
To learn more, you can find in our Privacy Policy.
Original paper

Big Data Mining of Energy Time Series for Behavioral Analytics and Energy Consumption Forecasting

Volume: 11, Issue: 2, Pages: 452 - 452
Published: Feb 20, 2018
Abstract
Responsible, efficient and environmentally aware energy consumption behavior is becoming a necessity for the reliable modern electricity grid. In this paper, we present an intelligent data mining model to analyze, forecast and visualize energy time series to uncover various temporal energy consumption patterns. These patterns define the appliance usage in terms of association with time such as hour of the day, period of the day, weekday, week,...
Paper Details
Title
Big Data Mining of Energy Time Series for Behavioral Analytics and Energy Consumption Forecasting
Published Date
Feb 20, 2018
Journal
Volume
11
Issue
2
Pages
452 - 452
TrendsPro
  • Scinapse’s Citation Trends graph enables the impact assessment of papers in adjacent fields.
  • Assess paper quality within the same journal or volume, irrespective of the year or field, and track the changes in the attention a paper received over time.
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
© 2025 Pluto Labs All rights reserved.
Step 1. Scroll down for details & analytics related to the paper.
Discover a range of citation analytics, paper references, a list of cited papers, and more.