Analyze Soft Measurement Technology Based Intelligent Algorithm in Sewage Treatment

Wen Cheng Wang; Zhong Xue Chen; Ke Li; Qin Zhou Niu

doi:10.4028/www.scientific.net/AMM.556-562.3164

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562Analyze Soft Measurement Technology Based...

Analyze Soft Measurement Technology Based Intelligent Algorithm in Sewage Treatment

Abstract:

On the basis of introduction to soft sensing technology, the paper comprehensively discusses the research present situation and the application characteristics of Genetic Algorithm、Artificial Neural Networks、and Support Vector Machine.After comparison and analysis, this paper presents a high quality research strategy of on-line real-time control.

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Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

3164-3167

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.3164

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Online since:

May 2014

Authors:

Wen Cheng Wang*, Zhong Xue Chen, Ke Li, Qin Zhou Niu

Keywords:

Intelligent Algorithm, Sewage Treatment, Soft Measurement, Virtual Instrument (VI)

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* - Corresponding Author

References

[1] Zhang Xinwen. Economic Model of Municipal Water Recycling and Technique Supporting System[D]. DaLian: Dalian University of Technology, (2006).

Google Scholar

[2] Yu Jinshou. Soft sensing Technology and Its Application[J]. Process Automation Instrumentation, 2008, 29(1) : 1 -7.

Google Scholar

[3] Li Lin. Application of PID Control Based on CMAC in Sewage Treatment[J]. Science Technology and Engineering, 2010, 10(10): 2574 -2576.

Google Scholar

[4] Zhu Xuefeng. Soft Measurement Technology and Application[J]. Journal of South China University(Natural Science Edition), 2002, 30( 11) : 61 -67.

Google Scholar

[5] Liu Xingzi, Lin Liang. Research Water Pollution Control System With Fuzzy Variables[J]. Fuzzy Systems and Mathematics, 2009, 23( 5) : 168-174.

Google Scholar

[6] Xu Guangni, Yu Jinshou. Application of Adaptive DNA Immune Algorithm in Chemical Soft Sensing[J]. Journal of East China University of Science and Technology (Natural Science Edition), 2009, 35( 1) : 139 -143.

Google Scholar

[7] Di Zhenzhen, Jiang Aiping. Application of Soft-sensing Technology based on Support Vector Machine[J], Process Automation Instrumentation, 2006, 27( 2) : 42 -45.

Google Scholar

[8] Lu Linhua. Research on Clustering Algorithms and its Application of the Fault Diagnosis of Wastewater Treatment Process[D]. Chongqing: Chongqing University, (2007).

Google Scholar

[9] Lv Qiang, Yu Jinshou. Soft Sensing Model Based on Quantum Neural Network and Its Application[J]. Journal of System Simulation, 2007, 19( 24) : 5696 -5699.

Google Scholar

[10] Cho，K H． Case Study on Rate-based Traffic Control Ofindustrial Networks Employing LonWorks ［J］． In-ternational Journal of Systems Science，2002, ( 3 ) : 161 -164.

DOI: 10.1080/00207720110091479

Google Scholar

[11] Wang Jimin, Peng Bo. Determine the Relevant Web Query Using Support Vector Regression[J]. Journal of South China University of Technology(Natural Science Edition), 2006，34( 6) : 74 -78，94.

Google Scholar