| Citation: | ZHAO H S,LIU F J,ZHANG X X,et al.Comparative study on inversion performance of optimization algorithms for the total emission accounting model of air pollutants in industrial parks[J].Journal of Environmental Engineering Technology，2024，14（4）：1232-1238 doi: 10.12153/j.issn.1674-991X.20230688
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Based on the total pollutant emission accounting model of industrial parks and taking the total VOCs emission accounting of a key petrochemical industry park on the southeast coast of China as an example, a comparative study of inversion performances was compared on three optimization algorithms, including Nelder-Mead simplex method (NM), dual annealing optimization algorithm (DA) and particle swarm optimization algorithm (PSO), under different random error intensity and number of failure sites. Besides, the inversion performance of three optimization objective functions constructed by deviation sum of squares (Objective Function 1), logarithm transformation (Objective Function 2) and hyperbolic cosine transformation (Objective Function 3) was compared. The results showed that the inversion performance of PSO was related to the number of particles, but the overall performance implied that it was not suitable for the inversion optimization under the current conditions. NM and DA had better inversion accuracy (MARE<30%), but the inversion computation efficiency of NM was about 11-20 times higher than that of DA, and NM had the best inversion performance. All the three optimization objective functions were suitable for inversion optimization under current conditions (MARE<30%). Objective Function 1 and Function 3 performed better when the random error intensity was small and the number of failure sites was small, while Objective Function 2 performed better when the random error intensity was relatively large and the number of failure sites was relatively large.
| [1] |
江苏省打好污染防治攻坚战指挥部办公室. 江苏省工业园区(集中区)污染物排放限值限量管理工作方案(试行)[A/OL]. (2021-07-19)[2023-09-15]. https://huanbao.bjx.com.cn/news/20210811/1169162.shtml.
|
| [2] |
杨喆, 李涛, 杨松柏, 等. 同时考虑监测和物料衡算的环境保护税税基核定方法[J]. 环境污染与防治,2019,41(5):608-610.
YANG Z, LI T, YANG S B, et al. Verification method of environmental protection tax base based on minitoring and material balance[J]. Environmental Pollution & Control,2019,41(5):608-610.
|
| [3] |
高新伟, 李瑶. 火电企业大气污染物排放量核算方法研究[J]. 环境科学与管理,2022,47(12):70-75. doi: 10.3969/j.issn.1673-1212.2022.12.015
GAO X W, LI Y. Calculation method and application of air pollutant emissions in thermal power companies[J]. Environmental Science and Management,2022,47(12):70-75. doi: 10.3969/j.issn.1673-1212.2022.12.015
|
| [4] |
白璐, 乔琦, 张玥, 等. 工业污染源产排污核算模型及参数量化方法[J]. 环境科学研究,2021,34(9):2273-2284.
BAI L, QIAO Q, ZHANG Y, et al. Pollutant generation and discharge accounting model and parameters quantification method in industrial sector[J]. Research of Environmental Sciences,2021,34(9):2273-2284.
|
| [5] |
胡瑞, 张学伟. 环境统计中污染物产生量排放量核算方法的探讨[J]. 科技视界,2012(34):115.
|
| [6] |
李贵林, 路学军, 陈程. 物料衡算法在工业源污染物排放量核算中的应用探讨[J]. 淮海工学院学报(自然科学版),2012,21(4):66-69.
LI G L, LU X J, CHEN C. Application of material balance algorithm to the accounting of industrial sources pollution emissions[J]. Journal of Huaihai Institute of Technology (Natural Science Edition),2012,21(4):66-69.
|
| [7] |
平措. 大气污染扩散长期模型的应用研究[D]. 天津: 天津大学, 2006.
|
| [8] |
董吉开, 杜文莉, 王冰, 等. 湍流状态下化学品扩散溯源中不同目标函数的影响分析[J]. 化工学报,2020,71(3):1163-1173.
DONG J K, DU W L, WANG B, et al. Investigating impacts of cost functions to atmospheric dispersion modeling and source term estimation in turbulent condition[J]. CIESC Journal,2020,71(3):1163-1173.
|
| [9] |
MAO S S, LANG J L, CHEN T, et al. Impacts of typical atmospheric dispersion schemes on source inversion[J]. Atmospheric Environment,2020,232:117572. doi: 10.1016/j.atmosenv.2020.117572
|
| [10] |
程桂香. 非线性最优化问题的一族新的罚函数方法研究[D]. 北京: 首都师范大学, 2006.
|
| [11] |
肖宏峰. 基于单纯形多向搜索的大规模进化优化算法[D]. 长沙: 中南大学, 2009.
|
| [12] |
MA D L, DENG J Q, ZHANG Z X. Comparison and improvements of optimization methods for gas emission source identification[J]. Atmospheric Environment,2013,81:188-198. doi: 10.1016/j.atmosenv.2013.09.012
|
| [13] |
胡峰, 郎建垒, 毛书帅, 等. 典型优化目标函数下源参数反演性能对比研究[J]. 中国环境科学,2021,41(5):2081-2089. doi: 10.3969/j.issn.1000-6923.2021.05.011
HU F, LANG J L, MAO S S, et al. Comparative study on source parameters inversion performance of typical cost functions[J]. China Environmental Science,2021,41(5):2081-2089. doi: 10.3969/j.issn.1000-6923.2021.05.011
|
| [14] |
毛书帅, 郎建垒, 陈添, 等. 多情景源排放参数反演下典型优化算法性能对比[J]. 北京工业大学学报,2020,46(4):369-376. doi: 10.11936/bjutxb2019100019
MAO S S, LANG J L, CHEN T, et al. Performance of typical optimization algorithms on inversing multi-scene source parameters[J]. Journal of Beijing University of Technology,2020,46(4):369-376. doi: 10.11936/bjutxb2019100019
|
| [15] |
马思琦. 高炉和二次污染物的对流扩散反问题[J]. 复旦学报(自然科学版),2009,48(2):231-237.
MA S Q. Inverse convection-diffusion problems of plumes and second contamination[J]. Journal of Fudan University (Natural Science),2009,48(2):231-237.
|
| [16] |
殷凤兰, 李功胜, 贾现正. 一个多点源扩散方程的源强识别反问题[J]. 山东理工大学学报(自然科学版),2011,25(2):1-5.
YIN F L, LI G S, JIA X Z. An inverse problem of determining magnitudes of multi-point sources in the diffusion equation[J]. Journal of Shandong University of Technology (Natural Science Edition),2011,25(2):1-5.
|
| [17] |
WANG J L, LIU J J, WANG B, et al. A new method for multi-point pollution source identification[J]. Atmospheric and Oceanic Science Letters,2021,14(6):100098. doi: 10.1016/j.aosl.2021.100098
|
| [18] |
张俊明, 袁鹏, 郭继香, 等. 基于MATLAB模拟的石化企业蒸馏装置泄漏扩散环境风险分析[J]. 环境工程技术学报,2013,3(3):259-265. doi: 10.3969/j.issn.1674-991X.2013.03.041
ZHANG J M, YUAN P, GUO J X, et al. Analysis of environmental risk of leakage and diffusion of distillation column in petrochemical enterprises based on MATLAB[J]. Journal of Environmental Engineering Technology,2013,3(3):259-265. doi: 10.3969/j.issn.1674-991X.2013.03.041
|
| [19] |
国家技术监督局, 国家环境保护局. 制定地方大气污染物排放标准的技术方法: GB/T 3840—91[S]. 北京: 中国标准出版社, 1991.
|
| [20] |
陈增强, 高艺博, 陈成功, 等. 基于差分进化-NM单纯形法的危化品泄漏源定位[J]. 中国安全生产科学技术,2022,18(5):90-95.
CHEN Z Q, GAO Y B, CHEN C G, et al. Location for leakage source of hazardous chemicals based on differential evolution-NM simplex method[J]. Journal of Safety Science and Technology,2022,18(5):90-95.
|
| [21] |
蒋璐, 李奇, 陈维荣, 等. 基于Nelder-Mead优化的PEMFC三阶RQ等效电路参数辨识研究[J]. 电源学报,2019,17(2):12-18.
JIANG L, LI Q, CHEN W R, et al. Research on parameter identification of third-order RQ equivalent circuit of PEMFC based on nelder-mead optimization[J]. Journal of Power Supply,2019,17(2):12-18.
|
| [22] |
YANG F W, CHEN J J, LIU Y C. Improved and optimized recurrent neural network based on PSO and its application in stock price prediction[J]. Soft Computing,2023,27(6):3461-3476. doi: 10.1007/s00500-021-06113-5
|
| [23] |
杨俊祺, 范晓军, 赵跃华, 等. 基于PSO-BP神经网络的山西省碳排放预测[J]. 环境工程技术学报,2023,13(6):2016-2024. doi: 10.12153/j.issn.1674-991X.20230190
YANG J Q, FAN X J, ZHAO Y H, et al. Prediction of carbon emissions in Shanxi Province based on PSO-BP neural network[J]. Journal of Environmental Engineering Technology,2023,13(6):2016-2024. doi: 10.12153/j.issn.1674-991X.20230190
|
| [24] |
苗建杰, 李德波, 李慧君, 等. 改进粒子群算法在燃煤电厂中的应用现状及展望[J]. 环境工程,2023,41(增刊1):354-362.
|
| [25] |
甘秋云, 李兢思, 杨佳翰. 冷却调度参数对模拟退火算法性能的影响分析[J]. 蚌埠学院学报,2023,12(5):47-52. doi: 10.3969/j.issn.2095-297X.2023.05.009
GAN Q Y, LI J S, YANG J H. Analysis of cooling scheduling parameters on performance of simulated annealing algorithm[J]. Journal of Bengbu University,2023,12(5):47-52. □ doi: 10.3969/j.issn.2095-297X.2023.05.009
|
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