Design and Implementation of Large-Scale Public Building Energy Consumption Monitoring Platform Based on BP Neural Network
With the rapid development of network technology, people are increasingly dependent on the internet. When BP neural network (BNN) performs simulation calculation, it has the advantages of fast training speed, high accuracy, and strong robustness and is widely used in large-scale public (LSP) buildin...
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| Veröffentlicht in: | Security and communication networks 2021-10, Vol.2021, p.1-9 |
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| container_title | Security and communication networks |
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| creator | Liu, Xiancheng Tian, Congxiang |
| description | With the rapid development of network technology, people are increasingly dependent on the internet. When BP neural network (BNN) performs simulation calculation, it has the advantages of fast training speed, high accuracy, and strong robustness and is widely used in large-scale public (LSP) building energy consumption (BEC) monitoring platforms (LPB). Therefore, the purpose of this paper to study the energy consumption monitoring platform of large public (LP) buildings is to better monitor the energy consumption of public buildings, so as to supplement or remedy at any time. This article mainly uses the data analysis method and the experimental method to carry on the relevant research and the system test to the BNN. The experimental results show that the monitoring system (MS) platform designed in this paper has real-time performance, and its time consumption is between 2 s and 3 s, and the data accords with theory and reality. |
| doi_str_mv | 10.1155/2021/6438909 |
| format | Article |
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When BP neural network (BNN) performs simulation calculation, it has the advantages of fast training speed, high accuracy, and strong robustness and is widely used in large-scale public (LSP) building energy consumption (BEC) monitoring platforms (LPB). Therefore, the purpose of this paper to study the energy consumption monitoring platform of large public (LP) buildings is to better monitor the energy consumption of public buildings, so as to supplement or remedy at any time. This article mainly uses the data analysis method and the experimental method to carry on the relevant research and the system test to the BNN. The experimental results show that the monitoring system (MS) platform designed in this paper has real-time performance, and its time consumption is between 2 s and 3 s, and the data accords with theory and reality.</description><identifier>ISSN: 1939-0114</identifier><identifier>EISSN: 1939-0122</identifier><identifier>DOI: 10.1155/2021/6438909</identifier><language>eng</language><publisher>London: Hindawi</publisher><subject>Access to information ; Algorithms ; Back propagation ; Back propagation networks ; Communication ; Construction ; Data analysis ; Data compression ; Design ; Energy consumption ; Internet of Things ; Monitoring ; Neural networks ; Neurons ; Principal components analysis ; Public buildings ; Software ; Statistical analysis</subject><ispartof>Security and communication networks, 2021-10, Vol.2021, p.1-9</ispartof><rights>Copyright © 2021 Xiancheng Liu and Congxiang Tian.</rights><rights>Copyright © 2021 Xiancheng Liu and Congxiang Tian. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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When BP neural network (BNN) performs simulation calculation, it has the advantages of fast training speed, high accuracy, and strong robustness and is widely used in large-scale public (LSP) building energy consumption (BEC) monitoring platforms (LPB). Therefore, the purpose of this paper to study the energy consumption monitoring platform of large public (LP) buildings is to better monitor the energy consumption of public buildings, so as to supplement or remedy at any time. This article mainly uses the data analysis method and the experimental method to carry on the relevant research and the system test to the BNN. 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| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Wiley Online Library Open Access; Alma/SFX Local Collection |
| subjects | Access to information Algorithms Back propagation Back propagation networks Communication Construction Data analysis Data compression Design Energy consumption Internet of Things Monitoring Neural networks Neurons Principal components analysis Public buildings Software Statistical analysis |
| title | Design and Implementation of Large-Scale Public Building Energy Consumption Monitoring Platform Based on BP Neural Network |
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