Big data driven smart energy management: From big data to big insights
By Kaile Zhou, Chao Fu, Shanlin Yang. 2016
740 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/bdbec0c80b73919a656125bbd32f71f602980706
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
Citations in the corpus
- Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities (2020, background): “…of BDACs toward renewal of technological capabilities can be found in a range of industries including healthcare [94,95], manufacturing [96,97], bank and financial institutions [98], energy and communication infrastructure providers [99], as well as in the oil and gas sector amongst others [100].”
- Literature review of Industry 4.0 and related technologies (2018, neutral): “To mention some, Zhou et al. (2016a) studied big data performance and better algorithms for programming of Industry 4.0 systems.”
- A review of machine learning in building load prediction (2021, neutral): “Zhou et al. [179] discussed the sources and characteristics of energy big data.”
- Application of Big Data and Machine Learning in Smart Grid, and Associated Security Concerns: A Review (2019, background): “Demand side management through bid data analysis has also caught much attention [85], [86].”