Forecasting the Short-Term Electricity Consumption of Building Using a Novel Ensemble Model

Autor: Shubing Shan, Buyang Cao, Zhiqiang Wu

Publikováno v: IEEE Access, Vol 7, Pp 88093-88106 (2019)

The accurate prediction approach of urban buildings' electricity consumption is an important foundation for smart urban energy management. It provides a decision basis for reasonable electricity deployments upon different scenarios. Usually, a single

Externí odkaz: https://doaj.org/article/56c337437e74481d800ca83dd21857ff

Forecasting the Short-Term Electricity Consumption of Building Using a Novel Ensemble Model

Autor: Buyang Cao, Shubing Shan, Zhiqiang Wu

Publikováno v: IEEE Access, Vol 7, Pp 88093-88106 (2019)

The accurate prediction approach of urban buildings' electricity consumption is an important foundation for smart urban energy management. It provides a decision basis for reasonable electricity deployments upon different scenarios. Usually, a single

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7eebee3bd940b86fe32a382178dbc77
https://doi.org/10.1109/access.2019.2925740

A Short-Term Forecast Approach of Public Buildings’ Power Demands upon Multi-source Data

Autor: Buyang Cao, Shubing Shan

Publikováno v: Lecture Notes in Computer Science
1st International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE)
1st International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE), Aug 2017, Reggio, Italy. pp.174-188, ⟨10.1007/978-3-319-66808-6_12⟩
Lecture Notes in Computer Science ISBN: 9783319668079
CD-MAKE

Part 3: MAKE Privacy; International audience; Due to the significant increase of the global electricity demand and the rising number of urban population, the electric consumption in a city has attracted more attentions. Given the fact that public bui

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2fefd74e93f4b7d0c06f755dac39f3ea
https://hal.inria.fr/hal-01677140/file/456304_1_En_12_Chapter.pdf

Forecasting the Degree of Crowding in Urban Public Open Space upon Multi-source Data

Autor: Shubing Shan, Buyang Cao

Publikováno v: ISCID (2)

As the urban population has risen steadily, it plays a major role in urban security and traffic control to make an accurate prediction of the degree of crowing in urban public open space. In this paper we propose an approach to predict the degree of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6cd8b5c9976ec77a0b19491af8f022ef
https://doi.org/10.1109/iscid.2016.2025