Assessment of leakage degree of underground heating primary pipe network based on chaotic simulated annealing neural network

Proceedings - 2017 Chinese Automation Congress, CAC 2017

Volumn 2017-January, Issue , 2017, Pages 5895-5900

  Jiao, Shang Bin ^a   Fan, Le ^a   Wu, Peng Yue ^b   Qiao, Lei ^b   Wang, Yi ^a   Xie, Guo ^a  

^a XI'AN UNIVERSITY OF TECHNOLOGY   (China)

^b XI AN THERMAL POWER RESEARCH INSTITUTE CO   (China)

Author keywords

Chaotic simulated annealing function; Competitive neural network; Degree of leakage assessment; Underground heating pipe network

Indexed keywords

PIPELINES; VOLTAGE MEASUREMENT;

ASSESSMENT MODELS; CHAOTIC SIMULATED ANNEALING; COMPETITIVE NEURAL NETWORK; LEAKAGE ASSESSMENT; NON-LINEAR RELATIONSHIPS; OUTPUT PARAMETERS; PHYSICAL QUANTITIES; UNDERGROUND HEATING;

SIMULATED ANNEALING;

EID: 85050272693     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CAC.2017.8243837     Document Type: Conference Paper

References (18)

1. Wang Jianshan, "Problems of heating network fault and improving reliability of heating network", Henan Science and Technology, vol. 21, 2015.
2. Lei Cuihong, Zou Pinghua, "Leak diagnosis of two stage BP neural network in heating network", Journal of HARBIN institute of technology, vol. 43, pp. 76-79, 2011.
3. Yin Shuo, "Research on safety evaluation and computer simulation of urban central heating system", Beijing: Beijing University of Civil Engineering and Architecture, 2014.
4. Yuan Zhaoqing, Liu Yingchun, Liu Yan, "Application of Fiber Bragg Grating in Thermal Pipeline Leakage Detection", Non-Destructive Testing, vol. 32(10), pp. 791-794, 2010.
5. Feng Yingjian, "Research on leak detection system of urban water supply network",Shenyang: Shenyang university of technology,2008.
6. Zhang Xiaofeng, Zhang Guangbin, Wang Caifeng, " Ultrasonic detection device and method for pipeline leakage", CN103292160A, 2013.
7. Gong Yan, Yuan Zongming, Lin Yu, "Sonic leak detection technology of oil and gas Pipeline", Pipeline Technique and Equipment, pp. 19-21, 2010.
8. Guo Shixu, Chen Shili, Huang Xinjing, "Development and Application of Microsele Detector for Submarine Pipeline", Modern Chemical Industry vol. 9, pp. 182-186, 2015.
9. Guo Tingting, "Research on some problems of spherical internal detector for pipeline", Tianjin: Tianjin University, 2011.
10. Cang Heng, Yan Huifeng, Cao yunfeng, "Research on Power Network Load Forecasting Based on Improved BP Neural Network", East China Science and Technology: Academic Edition, vol. 11, pp. 228-228, 2016.
11. Liu Fang, "Boiler Combustion Optimization Based on Neural Network and Genetic Algorithm", Baoding: North China Electric Power University, 2011.
12. You Lihua, Wu Jingjing, Wang Yao, "Prediction of pH based on simulated annealing optimized BP neural network", Journal of Transduction Technology, pp. 1643-1648, 2014.
13. Lin J S, "Power cable fault recognition based on an annealed chaotic competitive learning network", Algorithms, vol. 7, pp. 492-509, 2014.
14. Xu Y, Yang X., "A Class of Chaotic Neural Network with Morlet Wavelet Function Self-feedback", Bio-Inspired Computing and Applications. Springer Berlin Heidelberg, pp. 32-40, 2012.
15. Du K L, Swamy M N S, "Hopfield Networks, Simulated Annealing, and Chaotic Neural Networks", Neural Networks and Statistical Learning. Springer London, pp.159-186, 2014.
16. Atsalakis, Tsakalaki, "Simulating annealing and neural networks for chaotic time series forecasting",Chaotic Modeling & Simulation, vol. 1, pp. 81-90, 2012.
17. Atsalakis, Skiadas, D. Nezis, "Forecasting chaotic time series by a neural network", International Conference in Chaotic Modeling and Simulation, 2008.
18. Meng Fei, Pan Pengpeng,"Neural Network Based on Chaos PSO-BP Hybrid Algorithm", Computer Simulation, vol. 28(2), pp. 196-199, 2011.