Data-driven Modeling for Improved Residential Building Electricity Consumption Prediction and HVAC Efficiency Evaluation

Please use this identifier to cite or link to this item: http://tailieuso.udn.vn/handle/TTHL_125/9745

Full metadata record

DC Field	Value	Language
dc.contributor.advisor	Cetin, Kristen, Prof.	-
dc.contributor.author	Do, Thanh Huyen	-
dc.date.accessioned	2019-05-02T07:00:07Z	-
dc.date.available	2019-05-02T07:00:07Z	-
dc.date.issued	2018	-
dc.date.submitted	2019-04-24	-
dc.identifier.uri	http://tailieuso.udn.vn/handle/TTHL_125/9745	-
dc.description	Doctoral thesis. Major: Civil Engineering (Construction Engineering and Management); 146 pages	en
dc.description.tableofcontents	Chapter 1. Introduction; Chapter 2. Residential building energy consumption: A review of energy data availability, characteristics and energy performance prediction methods; Chapter 3. Evaluation of the causes and impact of outliers on residential building energy use prediction using inverse modeling; ...	en
dc.language.iso	en	en
dc.publisher	Iowa State University	en
dc.source	University of Science and Technology - The University of Danang	en
dc.subject	Residential building	en
dc.subject	Electricity consumption	en
dc.subject	HVAC	en
dc.subject	Prediction	en
dc.subject	Efficiency	en
dc.title	Data-driven Modeling for Improved Residential Building Electricity Consumption Prediction and HVAC Efficiency Evaluation	en
dc.title.alternative	Mô hình dữ liệu để cải thiện dự báo tiêu thụ điện tòa nhà dân cư và đánh giá hiệu quả HVAC	en
dc.type	Ph.D Thesis	en
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File	Description	Size	Format
DoThanhHuyen.TT.pdf	Abstract & Table of Contents	161.13 kB	Adobe PDF	View/Open
DoThanhHuyen.TV.pdf	Contents	5.15 MB	Adobe PDF	View/Open Request a copy