Journal of Guangxi Normal University(Natural Science Edition) ›› 2011, Vol. 29 ›› Issue (2): 219-222.

Previous Articles     Next Articles

Identification of Temperature Field in Intelligent Building Based on BP Network

CHENG Hong-mei1,2, ZHANG Zhen-ya1,3, ZHANG Shu-guang1   

  1. 1.School of Management,Universityof Science and Technology of China,Hefei Anhui 230026,China;
    2.School of Management,Anhui University of Architecture,Hefei Anhui 230022,China;
    3.Key Laboratory of Intelligent Building of Anhui Province,Anhui University of Architecture,Hefei Anhui 230022,China
  • Received:2011-05-10 Published:2018-11-19

Abstract: The identification of temperature filed of monitored region is one of the keysteps for the energy efficiency management in intelligent buildings.In this paper,the identification of temperature field in monitored region is treated as oneoptimization problem and feed forward neural network is adopted as the identification structure.To improve the performance of the identification model,input data of the desired neural network is normalized with minimum maximum methodas middle image and the normalized image of the input data is the stereographic projection of the middle image.To test the performance of the proposed identification model,BP and RBF neural networks are used as the desired feed forward neural network with temperature matrix for the infrared photograph in the experiment.Experiment results show that the performance of BP based temperature field identification model perporms well.

Key words: temperature field, identification, neural network, stereographic projection, normalization

CLC Number: 

  • TP391
[1] RALEGAONKAR R V,GUPTA R.Review of intelligent building construction:a passive solar architecture approach[J].Renewable and Sustainable Energy Reviews,2010,14(8):2238-2242.
[2] BRAUN J E.Intelligent building systems-past,present,and future[C]//Proceedings of the 2007 American Control Conference.New York:IEEE Press,2007:4374-4381.
[3] 李晋,秦琳琳,岳大志,等.试验温室温度系统建模与仿真[J].系统仿真学报,2008,20(7):1869-1875.
[4] 陆寅,苗克坚,何维.基于情境上下文感知的温度监测与警报系统[J].计算机应用,2009,29(2):583-585,594.
[5] DEO D S.Applications of expert system/neural networks/genetic algorithms in an intelligent building complex[J].Journal of the Institution of Engineers(India):Architectural Engineering Division,2006,87(10):4-9.
[6] 杨光友,刘琼.前向神经网络粒子群优化学习算法研究[J].广西师范大学学报:自然科学版,2008,26(3):151-156.
[7] CHEN Liang,FANG Qian-sheng,ZHANG Zhen-ya.Research on the identification of temperature in intelligent building based on feed forward neural network and particle swarm optimization algorithm[C]//Proceedings of 2010 International Conference on Natural Computation:Vol 4.Los Alamitos,CA:IEEE Computer Society,2010:1816-1820.
[1] MA Ling, LUO Xiaoshu, JIANG Pinqun. An Ink-jetted Code Character Recognition MethodBased on Probabilistic Neural Network [J]. Journal of Guangxi Normal University(Natural Science Edition), 2020, 38(4): 32-41.
[2] LI Yadai, WEI Duqu. Research on Firing Behavior of Magnetic Field Coupled Memristive Neural Network [J]. Journal of Guangxi Normal University(Natural Science Edition), 2020, 38(3): 19-24.
[3] YAN Hao, XU Hongbo, SHEN Yinghan, CHENG Xueqi. Research on Open Chinese Event Detection [J]. Journal of Guangxi Normal University(Natural Science Edition), 2020, 38(2): 64-71.
[4] YE Qing, HUANG Qiang, NIE Bin, LI Huan. An Adaptive High-Dimensional Outlier Recognition Method [J]. Journal of Guangxi Normal University(Natural Science Edition), 2020, 38(2): 107-114.
[5] LIU Xin, LUO Xiaoshu, ZHAO Shulin. Active Disturbance Rejection Control of Three-AxisStabilized Platform Based on BP Neural Network [J]. Journal of Guangxi Normal University(Natural Science Edition), 2020, 38(2): 115-120.
[6] TAN Anjie, WEI Duqu, QIN Yinghua. Research on Discharge Mode and Synchronization Behavior of Electromagnetic Field Coupled Memristor Neural Network [J]. Journal of Guangxi Normal University(Natural Science Edition), 2020, 38(1): 107-113.
[7] LUO Lan, ZHOU Nan, SI Jie. New Delay Partition Method for Robust Stability of Uncertain Cellular Neural Networks with Time-Varying Delays [J]. Journal of Guangxi Normal University(Natural Science Edition), 2019, 37(4): 45-52.
[8] FAN Rui, JIANG Pinqun, ZENG Shangyou, XIA Haiying, LIAO Zhixian, LI Peng. Design of Lightweight Convolution Neural Network Based on Multi-scale Parallel Fusion [J]. Journal of Guangxi Normal University(Natural Science Edition), 2019, 37(3): 50-59.
[9] XU Lunhui, CHEN Kaixun. Prediction of Road Network Speed Distribution Based on BP Neural Network Optimization by Improved Firefly Algorithm [J]. Journal of Guangxi Normal University(Natural Science Edition), 2019, 37(2): 1-8.
[10] ZHANG Jinlei, LUO Yuling, FU Qiang. Predicting Financial Time Series Based on Gated Recurrent Unit Neural Network [J]. Journal of Guangxi Normal University(Natural Science Edition), 2019, 37(2): 82-89.
[11] HUANG Liming,CHEN Weizheng,YAN Hongfei,CHEN Chong. A Stock Prediction Method Based on Recurrent Neural Network and Deep Learning [J]. Journal of Guangxi Normal University(Natural Science Edition), 2019, 37(1): 13-22.
[12] WU Wenya,CHEN Yufeng,XU Jin’an,ZHANG Yujie. High-level Semantic Attention-based Convolutional Neural Networks for Chinese Relation Extraction [J]. Journal of Guangxi Normal University(Natural Science Edition), 2019, 37(1): 32-41.
[13] LIN Yuan, LIU Haifeng, LIN Hongfei, XU Kan. Group Ranking Methods with Loss Function Incorporation [J]. Journal of Guangxi Normal University(Natural Science Edition), 2019, 37(1): 62-70.
[14] WANG Qi,QIU Jiahui,RUAN Tong,GAO Daqi,GAO Ju. Recurrent Capsule Network for Clinical Relation Extraction [J]. Journal of Guangxi Normal University(Natural Science Edition), 2019, 37(1): 80-88.
[15] ZOU Yanli,YAO Fei,WANG Yang,WANG Ruirui,WU Lingjie. Critical Node Identification for Power Systems Based on Network Structure and Power Tracing [J]. Journal of Guangxi Normal University(Natural Science Edition), 2019, 37(1): 133-141.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Guangxi Normal University(Natural Science Edition), All Rights Reserved.
Tel: 0773-5857325　E-mail: gxsdzkb@mailbox.gxnu.edu.cn
Powered by Beijing Magtech Co. Ltd