A prediction model for building energy consumption in a shopping mall based on Chaos theory
Considering the weakness of present prediction model on the traditional shopping mall building energy consumption caused by the limitations of the type and quantity of input variables, study proposes a shopping mall building energy consumption prediction model based on Chaos theory. This method firs...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-11-01
|
| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484722007600 |
| _version_ | 1797902002803441664 |
|---|---|
| author | Wenqiang Jing Meng Zhen Hongjie Guan Wei Luo XinYi Liu |
| author_facet | Wenqiang Jing Meng Zhen Hongjie Guan Wei Luo XinYi Liu |
| author_sort | Wenqiang Jing |
| collection | DOAJ |
| description | Considering the weakness of present prediction model on the traditional shopping mall building energy consumption caused by the limitations of the type and quantity of input variables, study proposes a shopping mall building energy consumption prediction model based on Chaos theory. This method firstly calculates the Lyapunov index of the energy consumption of the shopping mall to prove that the energy consumption of the shopping mall has chaotic characteristics. Secondly, it uses Chaos theory to reconstruct the phase space of the energy consumption data of the shopping mall to obtain the data with the energy consumption characteristics of the shopping mall as the data basis for the establishment of the model. Then the data is used to train the back-propagation (BP) neural network, and finally uses the confidence interval to describe the predicted value so as to complete the model building process. The RMSE of the model is reduced from 12.4 to 1.89, which proves the reliability of the algorithm. This method can provide a reference for building operation diagnostics and optimization. |
| first_indexed | 2024-04-10T09:10:54Z |
| format | Article |
| id | doaj.art-51ad1464ed294e95a3a39b747313cf13 |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-04-10T09:10:54Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-51ad1464ed294e95a3a39b747313cf132023-02-21T05:11:10ZengElsevierEnergy Reports2352-48472022-11-01853055312A prediction model for building energy consumption in a shopping mall based on Chaos theoryWenqiang Jing0Meng Zhen1Hongjie Guan2Wei Luo3XinYi Liu4Eurasian College, Eurasian Institute of Human Settlements, Xi’an 710055, PR China; Corresponding author.Department of Architecture, School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, ChinaEurasian College, Eurasian Institute of Human Settlements, Xi’an 710055, PR ChinaEurasian College, Eurasian Institute of Human Settlements, Xi’an 710055, PR ChinaXi’an University of Architecture and Technology, College of Materials Science and Engineering, Xi’an, 710055, PR ChinaConsidering the weakness of present prediction model on the traditional shopping mall building energy consumption caused by the limitations of the type and quantity of input variables, study proposes a shopping mall building energy consumption prediction model based on Chaos theory. This method firstly calculates the Lyapunov index of the energy consumption of the shopping mall to prove that the energy consumption of the shopping mall has chaotic characteristics. Secondly, it uses Chaos theory to reconstruct the phase space of the energy consumption data of the shopping mall to obtain the data with the energy consumption characteristics of the shopping mall as the data basis for the establishment of the model. Then the data is used to train the back-propagation (BP) neural network, and finally uses the confidence interval to describe the predicted value so as to complete the model building process. The RMSE of the model is reduced from 12.4 to 1.89, which proves the reliability of the algorithm. This method can provide a reference for building operation diagnostics and optimization.http://www.sciencedirect.com/science/article/pii/S2352484722007600Energy consumptionChaos characteristicForecast modelBP neural networkShopping mall building |
| spellingShingle | Wenqiang Jing Meng Zhen Hongjie Guan Wei Luo XinYi Liu A prediction model for building energy consumption in a shopping mall based on Chaos theory Energy Reports Energy consumption Chaos characteristic Forecast model BP neural network Shopping mall building |
| title | A prediction model for building energy consumption in a shopping mall based on Chaos theory |
| title_full | A prediction model for building energy consumption in a shopping mall based on Chaos theory |
| title_fullStr | A prediction model for building energy consumption in a shopping mall based on Chaos theory |
| title_full_unstemmed | A prediction model for building energy consumption in a shopping mall based on Chaos theory |
| title_short | A prediction model for building energy consumption in a shopping mall based on Chaos theory |
| title_sort | prediction model for building energy consumption in a shopping mall based on chaos theory |
| topic | Energy consumption Chaos characteristic Forecast model BP neural network Shopping mall building |
| url | http://www.sciencedirect.com/science/article/pii/S2352484722007600 |
| work_keys_str_mv | AT wenqiangjing apredictionmodelforbuildingenergyconsumptioninashoppingmallbasedonchaostheory AT mengzhen apredictionmodelforbuildingenergyconsumptioninashoppingmallbasedonchaostheory AT hongjieguan apredictionmodelforbuildingenergyconsumptioninashoppingmallbasedonchaostheory AT weiluo apredictionmodelforbuildingenergyconsumptioninashoppingmallbasedonchaostheory AT xinyiliu apredictionmodelforbuildingenergyconsumptioninashoppingmallbasedonchaostheory AT wenqiangjing predictionmodelforbuildingenergyconsumptioninashoppingmallbasedonchaostheory AT mengzhen predictionmodelforbuildingenergyconsumptioninashoppingmallbasedonchaostheory AT hongjieguan predictionmodelforbuildingenergyconsumptioninashoppingmallbasedonchaostheory AT weiluo predictionmodelforbuildingenergyconsumptioninashoppingmallbasedonchaostheory AT xinyiliu predictionmodelforbuildingenergyconsumptioninashoppingmallbasedonchaostheory |