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Joint Household Characteristic Prediction via Smart Meter Data
Sun G(孙干); Cong Y(丛杨); Hou DD(侯冬冬); Fan HJ(范慧杰); Xu XW(徐晓伟); Yu HB(于海斌)
作者部门机器人学研究室
关键词Household Characteristics Multi-task Learning Classification Problem Gaussian Process Smart Meter Data
发表期刊IEEE Transactions on Smart Grid
ISSN1949-3053
2018
页码1-11
收录类别EI
EI收录号20175004531749
产权排序1
摘要

Predicting specific household characteristics (e.g., age of person, household income, cooking style, etc) from their everyday electricity consumption (i.e., smart meter data) enables energy provider to develop many intelligent business applications or help consumers to reduce their energy consumption. However, most existing works intend to predict single household characteristic via smart meter data independently, and ignore the joint analysis of different characteristics. In this paper, we consider each characteristic as an independent task and intend to predict multiple household characteristics simultaneously by designing a new multi-task learning formulation: Discriminative Multi- Task Relationship Learning (DisMTRL). Specifically, two main challenges need to be handled: 1) task relationship, that is the embedded structure of relationships among different characteristics; 2) feature learning, there exist redundant features in original training data. To achieve these, our DisMTRL model aims to obtain a simple but robust weight matrix through capturing the intrinsic relatedness among different characteristics by task covariance matrix (MTRL) and incorporating the discriminative features via feature covariance matrix (Dis). For model optimization, we employ an alternating minimization strategy to learn the optimal weight matrix as well as the relationship between tasks by converting feature learning regularization as trace minimization problem. For evaluation, we adopt a smart meter dataset collected from 4232 households in Ireland at a 30min granularity over an interval of 1.5 years. The experimental results justify the effectiveness of our proposed model.

语种英语
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/21395
专题机器人学研究室
通讯作者Cong Y(丛杨)
作者单位1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences, China
3.Department of Information Science, University of Arkansas at Little Rock, USA
推荐引用方式
GB/T 7714
Sun G,Cong Y,Hou DD,et al. Joint Household Characteristic Prediction via Smart Meter Data[J]. IEEE Transactions on Smart Grid,2018:1-11.
APA Sun G,Cong Y,Hou DD,Fan HJ,Xu XW,&Yu HB.(2018).Joint Household Characteristic Prediction via Smart Meter Data.IEEE Transactions on Smart Grid,1-11.
MLA Sun G,et al."Joint Household Characteristic Prediction via Smart Meter Data".IEEE Transactions on Smart Grid (2018):1-11.
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