Environment Air Quality Evaluation System Based on Genetic Arithmetic and BP Neural Network

Air is an important condition for everything on earth to exist. Environment air quality influences the zoology balance, health of human beings and society development. An environment air quality evaluation system is presented in this paper. In this system, temperature, humidity and pollution concentration are the original parameters. A modeling method based on genetic neural network was adopted to evaluate environment air quality. The environment air quality can be classified into 3 categories: good, common and bad. Environment air quality evaluation class will be obtained according to the result of modeling. Alarm will be given when the concentration of nocuous gas beyond the standard, so blast and fire can be efficiently avoided. Environment air quality will be real-time monitor by using this system. The experimental results show that this system is feasible and effective and this modeling method has great application foreground in the environment air evaluation.