Advances and challenges in building engineering and data mining applications for energy-efficient communities
Bibliographic Data
| ID | 21228472 |
|---|---|
| Authors | Zhun Yu (Hunan University), Fariborz Haghighat (0000-0003-2869-7308, Concordia University, corresponding author), Benjamin C M Fung (0000-0001-8423-2906, McGill University) |
| Year | 2016 |
| Volume | 25 |
| Pages | 33-38 |
| Publication date | 2016-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sustainable Cities and Society (JOURNAL) |
| Journal identifiers | ISSN: 2210-6707 • E-ISSN: 2210-6715 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.scs.2015.12.001 |
| OpenAlex | W2204655733 |
| Language | EN |
| Citations received | 22 |
| References cited | 41 |
The rapidly growing and gigantic body of stored data in the building field, coupled with the need for data analysis, has generated an urgent need for powerful tools that can extract hidden but useful knowledge of building performance improvement from large data sets. As an emerging subfield of computer science, data mining technologies suit this need well and have been proposed for relevant knowledge discovery in the past several years. Aimed to highlight recent advances, this paper provides an overview of the studies undertaking the two main data mining tasks (i.e. predictive tasks and descriptive tasks) in the building field. Based on the overview, major challenges and future research trends are also discussed
Data mining · Data science · Knowledge extraction · Air Quality Monitoring and Forecasting · Building Energy and Comfort Optimization · Computer Science · Energy Load and Power Forecasting
Comparing data mining methods for predicting cost construction projects
Field study on energy economic assessment of office buildings envelope retrofitting in southern China
Dynamic programming and genetic algorithms to control an HVAC system
Regional integration and city-level energy efficiency
Hidden Markov Models for indirect classification of occupant behaviour
Fog computing for sustainable smart cities in the IoT era
Identifying Hard-to-Decarbonize houses from multi-source data in Cambridge, UK
Improving sustainable office building operation by using historical data and linear models to predict energy usage
A non-intrusive load monitoring system using multi-label classification approach
Bricks
Shunt active power filter
Control, regulation and optimization of bidirectional energy flows for electric vehicles’ charging and discharging
Motif-based association rule mining and clustering technique for determining energy usage patterns for smart meter data
Fusing TensorFlow with building energy simulation for intelligent energy management in smart cities
Data analytics for occupancy pattern learning to reduce the energy consumption of HVAC systems in office buildings
Low power convolutional architectures
Multi-criteria comprehensive study on predictive algorithm of hourly heating energy consumption for residential buildings
A study on semi-supervised learning in enhancing performance of AHU unseen fault detection with limited labeled data
Energy disaggregation of overlapping home appliances consumptions using a cluster splitting approach
Monitoring and control of energy consumption in buildings using WoT
Occupant presence and behavior
Overview on failures of urban underground infrastructures in complex geological conditions due to heavy rainfall in China during 1994–2018
| Unique citing works | 22 |
|---|---|
| Citations per year | 2.2 |
| Citation span | 2016 - 2024 (9) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 22 |