阶梯网络与多任务学习对台湾地区能量分解的实证研究

Fang-Yi Chang, Chun-An Chen, Shou-De Lin
{"title":"阶梯网络与多任务学习对台湾地区能量分解的实证研究","authors":"Fang-Yi Chang, Chun-An Chen, Shou-De Lin","doi":"10.1109/TAAI.2018.00028","DOIUrl":null,"url":null,"abstract":"Energy disaggregation is a technique of estimation electricity consumption of individual appliance from an aggre-gated meter. In this paper, we study ladder network [6] and multitask learning on energy disaggregation using auto-encoder architecture. This auto-encoder architecture was proposed fromKelly and Knottenbelt in their recent research work [1]. We used this auto-encoder architecture to the high-ownership appliances, air conditioner, bottle warmer, fridge, television and washing machine, in Taiwan and evaluated the effectiveness of the ladder network and multitask learning via these five appliances. The experimental data set has collected by Institute For InformationIndustry. We expect that this project can promote the industrial development of big data-driven smart energy management inTaiwan.","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"An Empirical Study of Ladder Network and Multitask Learning on Energy Disaggregation in Taiwan\",\"authors\":\"Fang-Yi Chang, Chun-An Chen, Shou-De Lin\",\"doi\":\"10.1109/TAAI.2018.00028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Energy disaggregation is a technique of estimation electricity consumption of individual appliance from an aggre-gated meter. In this paper, we study ladder network [6] and multitask learning on energy disaggregation using auto-encoder architecture. This auto-encoder architecture was proposed fromKelly and Knottenbelt in their recent research work [1]. We used this auto-encoder architecture to the high-ownership appliances, air conditioner, bottle warmer, fridge, television and washing machine, in Taiwan and evaluated the effectiveness of the ladder network and multitask learning via these five appliances. The experimental data set has collected by Institute For InformationIndustry. We expect that this project can promote the industrial development of big data-driven smart energy management inTaiwan.\",\"PeriodicalId\":211734,\"journal\":{\"name\":\"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAAI.2018.00028\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAAI.2018.00028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

能量分解是一种从汇总电表估算单个电器用电量的技术。本文研究了阶梯网络[6]和基于自编码器结构的能量分解多任务学习。这种自编码器架构是由kelly和Knottenbelt在他们最近的研究工作中提出的[1]。我们将这种自编码器架构应用于台湾的高拥有率家电,空调、暖瓶器、冰箱、电视和洗衣机,并通过这五种家电评估梯子网络和多任务学习的有效性。实验数据集由信息工业研究所收集。我们期待这个项目能够推动大数据驱动的智慧能源管理在台湾的产业发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
An Empirical Study of Ladder Network and Multitask Learning on Energy Disaggregation in Taiwan
Energy disaggregation is a technique of estimation electricity consumption of individual appliance from an aggre-gated meter. In this paper, we study ladder network [6] and multitask learning on energy disaggregation using auto-encoder architecture. This auto-encoder architecture was proposed fromKelly and Knottenbelt in their recent research work [1]. We used this auto-encoder architecture to the high-ownership appliances, air conditioner, bottle warmer, fridge, television and washing machine, in Taiwan and evaluated the effectiveness of the ladder network and multitask learning via these five appliances. The experimental data set has collected by Institute For InformationIndustry. We expect that this project can promote the industrial development of big data-driven smart energy management inTaiwan.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Ant Colony Optimization with Negative Feedback for Solving Constraint Satisfaction Problems Using Machine Learning Algorithms in Medication for Cardiac Arrest Early Warning System Construction and Forecasting Using AHP to Choose the Best Logistics Distribution Model A Vector Mosquitoes Classification System Based on Edge Computing and Deep Learning Deep Recurrent Q-Network with Truncated History
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1