Title :
Design of Early Warning System of PM2.5 Detection Based on BP Neural
Author :
Zhao Bing-Chen ; Huang Jun-Ying ; Zhang Bin ; Zhang Xiao-Jing
Author_Institution :
XingTai Univ., Xingtai, China
Abstract :
The issue of PM2.5 is becoming a popular atmospheric research hotpot recently. This particular paper evaluates the era reasons as well as influencing factors associated with PM2.5 based on the information associated with PM2.5 in Xing Tai (2014. 01. 01 - 2014. 04. 26), and builds the actual era as well as evolution mode of PM2.5 in Xing Tai by utilizing evolutionary algorithms formula and BP neuron logical network. Lastly, the actual model´s effectiveness, versatility as well as reliability tend to be validated by experiments.
Keywords :
atmospheric composition; atmospheric techniques; neural nets; reliability; PM2.5 BP neuron logical network; PM2.5 detection; PM2.5 evolution mode; XingTai; atmospheric research; early warning system; evolutionary algorithms formula; model effectiveness; reliability; Biological neural networks; Data models; Genetic algorithms; Mathematical model; Neurons; Predictive models; Training; atmospheric research; evolutionary algorithms; neural logical network;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2014 7th International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-6635-6
DOI :
10.1109/ICICTA.2014.50
