Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Kang, Zhaoyi"'
Autor:
Kang, Zhaoyi, Spanos, Costas J.
Sequential or online dimensional reduction is of interests due to the explosion of streaming data based applications and the requirement of adaptive statistical modeling, in many emerging fields, such as the modeling of energy end-use profile. Princi
Externí odkaz:
http://arxiv.org/abs/1407.4430
In this paper, the modeling of building end-use energy profile is comprehensively investigated. Top-down and Bottom-up approaches are discussed with a focus on the latter for better integration with occupant information. Compared to the Time-Of-Use (
Externí odkaz:
http://arxiv.org/abs/1406.6133
Autor:
Chan, Mei Lin, Yoxall, Brian, Park, Hyunkyu, Kang, Zhaoyi, Izyumin, Igor, Chou, Jeffrey, Megens, Mischa M., Wu, Ming C., Boser, Bernhard E., Horsley, David A.
Publikováno v:
In Sensors & Actuators: A. Physical April 2012 177:1-9
Autor:
Kang, Zhaoyi
Publikováno v:
Kang, Zhaoyi. (2015). Efficient Multi-Level Modeling and Monitoring of End-use Energy Profile in Commercial Buildings. UC Berkeley: Electrical Engineering & Computer Sciences. Retrieved from: http://www.escholarship.org/uc/item/1867c6vm
In this work, modeling and monitoring of end-use power consumption in commercial buildings are investigated through both Top-Down and Bottom-Up approaches. In the Top-Down approach, an adaptive support vector regression (ASVR) model is developed to a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______325::9d10600272e8e4015aa8c221d7e422fa
http://n2t.net/ark:/13030/m59w3k26
http://n2t.net/ark:/13030/m59w3k26
Publikováno v:
Jin, Ming; Jin, Ruoxi; Kang, Zhaoyi; Konstantakopoulos, Ioannis C; & Spanos, Costas J. (2014). PresenceSense: Zero-training Algorithm for Individual Presence Detection based on Power Monitoring. Buildsys Conference '14. UC Berkeley: Center for Research in Energy Systems Transformation (CREST). Retrieved from: http://www.escholarship.org/uc/item/4df8x2kq
Non-intrusive presence detection of individuals in commercial buildings is much easier to implement than intrusive methods such as passive infrared, acoustic sensors, and camera. Individual power consumption, while providing useful feedback and motiv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______325::0bd86216d2762784788c4e41a019e0cb
http://www.escholarship.org/uc/item/4df8x2kq
http://www.escholarship.org/uc/item/4df8x2kq
Publikováno v:
Kang, Zhaoyi; Zhou, Yuxun; Zhang, Lin; & Spanos, Costas J. (2014). Virtual Power Sensing Based on a Multiple-Hypothesis Sequential Test. IEEE SmartGridComm 2013 Symposium-The Whole Picture-Sense, Communicate, Compute, Control. UC Berkeley: Center for Research in Energy Systems Transformation (CREST). Retrieved from: http://www.escholarship.org/uc/item/7rg0b8kr
Virtual-Sensing, which is achieved through the disaggregation of composite power metering signals, is a solution towards achieving fine-grained smart power monitoring. In this work we discuss the challenging issues in Virtual-Sensing, introduce and u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______325::2e2092e4e7e25568cbfb8fd4d1185794
http://www.escholarship.org/uc/item/7rg0b8kr
http://www.escholarship.org/uc/item/7rg0b8kr
Publikováno v:
2013 IEEE International Conference on Smart Grid Communications (SmartGridComm); 2013, p785-790, 6p
Publikováno v:
2013 IEEE International Conference on Automation Science & Engineering (CASE); 2013, p593-598, 6p
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