系统仿真学报 ›› 2020, Vol. 32 ›› Issue (11): 2226-2234.doi: 10.16182/j.issn1004731x.joss.19-FZ0510E

• 仿真模型/系统置信度评估技术 • 上一篇    下一篇

面向空气质量数据分析的广义零膨胀二项模型研究

苏本跃1,3, 徐鹏鹏2,3, 盛敏3,4   

  1. 1.铜陵学院数学与计算机学院,安徽铜陵 244061;
    2.安庆师范大学计算机与信息学院,安徽安庆 246133;
    3.安徽省智能感知与计算重点实验室,安徽安庆 246133;
    4.安庆师范大学数学与计算科学学院,安徽安庆 246133
  • 收稿日期:2019-02-10 修回日期:2019-09-08 出版日期:2020-11-18 发布日期:2020-11-17

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

Su Benyue1,3, Xu Pengpeng2,3, Sheng Min3,4   

  1. 1.School of Mathematics and Computer,Tongling University,Tongling 244061,China;
    2.School of Computer and Information,Anqing Normal University,Anqing 246133,China;
    3.The University Key Laboratory of Intelligent Perception and Computing of Anhui Province,Anqing 246133,China;
    4.School of Mathematics and Computational Science,Anqing Normal University,Anqing 246133,China
  • Received:2019-02-10 Revised:2019-09-08 Online:2020-11-18 Published:2020-11-17
  • About author:Su Benyue(1971-),Male,Wuhu,Ph.D.,professor,research direction:statistical computing and statistical pattern recognition.
  • Supported by:
    National Nature Science Foundation of China(11475003), Science and Technology Major Project of Anhui Province (18030901021), Anhui Provincial Department of Education outstanding top-notch talent-funded projects ( gxbjZD26)

摘要: 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。

关键词: 计数模型, 改进二项分布, 零膨胀, 零膨胀二项回归模型, 空气质量分析

Abstract: 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.

Key words: count model, generalized binomial distribution, zero-inflated model, zero-inflated binomial regression model, air quality analysis

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