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

机译:基于遗传算法和BP神经网络的环境空气质量评价系统。

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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.
机译:空气是地球上一切事物存在的重要条件。环境空气质量影响生态平衡,人类健康和社会发展。本文提出了一种环境空气质量评价系统。在该系统中,温度,湿度和污染浓度是原始参数。采用基于遗传神经网络的建模方法对环境空气质量进行评估。环境空气质量可分为三类:好,普通和差。根据建模结果获得环境空气质量评价等级。当有毒气体的浓度超过标准时,将发出警报,从而可以有效避免爆炸和火灾。使用此系统将实时监控环境空气质量。实验结果表明,该系统可行可行,建模方法在环境空气评价中具有广阔的应用前景。

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