Indoor Air Quality Assessment Based on Genetic Artificial Neural Network

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Abstract:

A new method for indoor air quality assessment with training artificial neural network prediction model was presented. Genetic algorithm was used to train artificial neural network prediction model in this method. The train sample for artificial neural network learning model was grading standard. According to the weight and threshold after network study, this method could be used to make assessment on indoor air quality. The example of indoor air quality assessment demonstrated that this method improved prediction precision. This assessment method is more accurate than the traditional assessment methods. Moreover, it has the ability of global optimization, self-learning, self-adaption. This algorithm overcomes the shortcomings of traditional BP artificial neural network algorithm.

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Periodical:

Advanced Materials Research (Volumes 726-731)

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1147-1150

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Online since:

August 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Guiquan TIAN: Research of Environmental Sciences. Vol. 9 (1996), p.45

Google Scholar

[2] Zhizhen WANG, Jingfang Bai: Application of grey system and fuzzy mathematics in environmental protection (Harbin Institute of Technology press, Harbin 2007).

Google Scholar

[3] Baosong Liang, Dianli CAO: Fuzzy mathematics and its application (Science Press, Beijing 2007).

Google Scholar

[4] Cho, BC, etc: Water Science &Technology. Vol.44(2001), p.95

Google Scholar

[5] Jun GAO: Artificial neural network theory and simulation examples (China Machine Press, Beijing 2003) .

Google Scholar

[6] Hongfang WANG, et al: Science Technology and Engineering. Vol.9(2009), p. (1997)

Google Scholar

[7] Shenglong KUAI, et al: Journal of Shenyang University. Vol.18(2006), p.43

Google Scholar