云环境下基于改进SEIRS模型的VOCs最优减排计算

Calculation of Optimal VOCs Emission Reduction Based on Improved SEIRS Model in Cloud Environment

不同区域的挥发性有机物(volatile organic compounds, VOCs)排放是相互关联与影响的,为了将VOCs对大气环境的影响降到最低,实现VOCs区域协同联动治理,建立了以VOCs减排总量最大为首要目标最优减排模型,提出一种考虑环境污染因素的改进SEIRS传染病动力学优化算法(SEIRS infectious disease dynamics optimization algorithm considering environmental pollution,SEIRSCE)在云环境下求解模型。应用案例以西安市为例,在阿里云服务器中使用SEIRS-CE算法对西安市13个气象监测站所对应VOCs关联区域减排问题进行计算并与传统智能优化算法进行对比,结果表明建立的VOCs最优减排模型具有科学性和可行性,在云环境下使用SEIRS-CE算法相较于对比算法求解VOCs最优减排问题的收敛速度更快,求解精度更高,陷入局部陷阱概率更低,具有高并发性、高安全性、高共享性,对府际间VOCs联防联控治理提供借鉴。

Volatile organic compounds(VOCs)emissions in different regions are correlated and influenced.In order to minimize the impact of VOCs on the atmospheric environment and achieve synergistic governance of VOCs regions,an optimal emission reduction model is established with the maximum VOCs emission reduction as the primary goal.An improved SEIRS infectious disease dynamics optimization algorithm considering environmental pollution(SEIRS-CE)is proposed and the model is solved in cloud environment.Taking Xi'an city as an example,the SEIRS-CE algorithm is used in Ali cloud server to calculate the emission reduction of VOCs associated with 13 meteorological monitoring stations in Xi'an city and compared with the traditional intelligent optimization algorithm.The results show that the established VOCs optimal emission reduction model is scientific and feasible.Compared with the contrast algorithm,the SEIRS-CE algorithm in cloud environment can solve the VOCs optimal emission reduction problem with faster convergence speed,higher solution accuracy,lower probability of falling into local trap,with high concurrency,high security,high sharing,and provide reference for the joint prevention and control of VOCs among the government.