面向空气质量数据分析的广义零膨胀二项模型研究

针对化工园区气体超标排放的质量监控和超排计数问题,构建了广义零膨胀二项分布模型。在统计气体超标排放次数时,发现超标次数具有典型的零膨胀特征。传统的零膨胀泊松模型和负二项回归模型等会低估零膨胀概率,将传统的二项回归模型推广到更为一般的形式,构建了广义零膨胀二项分布模型。该模型满足了期望小于方差的特性,较好解决了超标排放中出现的既有过离散又有零膨胀的问题。实验表明,广义零膨胀二项分布模型具有较好的拟合效果,适应性和鲁棒性均较强。

Generalized Zero-inflated Binomial Distribution Model Aimed at Air Quality Data Analysis

For the problem of the quality monitoring and counting of excessive gas emissions in chemical industry parks, a generalized zero-inflated binomial distribution model is constructed. Statistics show that the times of number of excessive gas emissions has a typical zero-inflated feature. The traditional zero-inflated Poisson model and negative binomial regression model and so on will underestimate the probability of zero inflation. A generalized zero-inflated binomial distribution model is constructed by extending the traditional binomial regression model to a more general form. This model satisfies the characteristic that the expectation is less than the variance, and better solves the problems of both over-dispersed and zero-inflated in excessive gas emissions. Experiments show that the generalized zero-flated binomial distribution model has a good fitting effect, strong adaptability and robustness.