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GA-BP Air Quality Evaluation Method Based on Fuzzy Theory

机译:基于模糊理论的GA-BP空气质量评价方法

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摘要

With the rapid development of China's economy, the scale of the city has been continuously expanding, industrial enterprises have been increasing, the discharge of multiple pollutants has reached the top of the world, and the environmental problems become more and more serious. The air pollution problem is particularly prominent. Air quality has become a daily concern for people. In order to control air pollution, it is necessary to grasp the air quality situation in an all-round way. It is necessary to evaluate air quality. Accurate results of air quality evaluation can help people know more about air quality. In this paper, refers to previous research results and different evaluation methods, combined with artificial neural network, fuzzy theory, genetic algorithm, GA-BP hybrid algorithm based on fuzzy theory is proposed to evaluate air quality. At the same time, for the problem that the two-grade standard of air quality annual evaluation is not suitable for practical application, the four-grade standard for annual air quality evaluation has been proposed, and its practicality has been verified through experiments. By setting contrast experiments and comparing the air quality evaluation model based on standard BP algorithm, it is proved that the fuzzy GA-BP evaluation model is better than the standard BP model, both in efficiency and accuracy.
机译:随着中国经济的快速发展,城市规模不断扩大,工业企业不断壮大,多种污染物的排放量已达到世界首位,环境问题也越来越严重。空气污染问题尤为突出。空气质量已成为人们每天关注的问题。为了控制空气污染,有必要全面掌握空气质量状况。有必要评估空气质量。准确的空气质量评估结果可以帮助人们更多地了解空气质量。本文参考以往的研究成果和不同的评价方法,结合人工神经网络,模糊理论,遗传算法,基于模糊理论的GA-BP混合算法对空气质量进行评价。同时,针对二级空气质量年度评价标准不适合实际应用的问题,提出了年度空气质量四级评价标准,并通过实验验证了其实用性。通过设置对比实验并比较基于标准BP算法的空气质量评价模型,证明了模糊GA-BP评价模型在效率和准确性上均优于标准BP模型。

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