Revealing Household Characteristics from Smart Meter Data

By Christian Beckel, Leyna Sadamori, Thorsten Staake, Silvia Santini. 2014

300 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Global and Planetary Change, Transportation

View Paper: https://www.semanticscholar.org/paper/f204b7724e2394b6af9d3ab3d9b974b43c6a410a

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. Chongqing Kang
2. Qixin Chen
3. Yi Wang
4. Tao Hong
5. Stephen A. Haben
6. Peter Grindrod
7. Colin Singleton
8. Rafal Weron

In Global and Planetary Change

1. Tao Hong

In Transportation

1. Chongqing Kang
2. Yi Wang
3. Qixin Chen

Citations in the corpus

• Analysis and Clustering of Residential Customers Energy Behavioral Demand Using Smart Meter Data (2016, methodology): “models [13], [20], principle component analysis [25], self organizing maps [11], and spectral clustering [21].”
• Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges (2018, methodology): “and comparisons with SVM and traditional CLASS proposed in [35] were conducted.”