Understanding household energy consumption behavior: The contribution of energy big data analytics

By Kaile Zhou, Shanlin Yang. 2016

388 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Management, Monitoring, Policy and Law

View Paper: https://www.semanticscholar.org/paper/0015cfaf4bcf21ab18553ee8c0ca1fb71458d078

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Simona D'Oca
2. Fuad Un-Noor
3. Tianzhen Hong
4. Zsofia Deme Belafi
5. Chien-fei Chen
6. Eklas Hossain

In Management, Monitoring, Policy and Law

1. Simona D'Oca
2. Tianzhen Hong
3. Zsofia Deme Belafi
4. Chien-fei Chen

Citations in the corpus

• Synthesizing building physics with social psychology: An interdisciplinary framework for context and occupant behavior in office buildings (2017, positive): “Supported by the vast amount of available energy consumption and human-related data, together with the advancements in big data analysis techniques, scholars [20] proposed an interdisciplinary research framework at the boundaries of energy and social sciences bounded with data information science.”
• Application of Big Data and Machine Learning in Smart Grid, and Associated Security Concerns: A Review (2019, background): “[157] Y. Liu, J. Shi, Y. Yang, and W.-J. Lee, ‘‘Short-term wind-power prediction based on wavelet transform–support vector machine and statistic-characteristics analysis,’’ IEEE Trans.”
• AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives (2022, background): “2014; Zhou and Yang 2016; Aste et al.”