Calibration of the activated sludge model with genetic algorithms. Part II. Analysis of results

被引：0

作者：

Urban, Rafal ^{[1
]}

Szetela, Ryszard ^{[1
]}

机构：

[1] Wroclaw Univ Technol, Inst Environm Protect Engn, PL-50370 Wroclaw, Poland

来源：

ENVIRONMENT PROTECTION ENGINEERING | 2007年 / 33卷 / 01期

关键词：

D O I：

暂无

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

In a previous article [1], a method for the calibration of activated sludge model No. 1 (ASM 1) based on genetic algorithms is proposed. For the needs of calibration, use was made of 153 objective functions. For some objective functions, the results obtained differ from expected values. In this article, additional analyses are presented to explain the inconsistencies in the results. Both the methods presented are based on a series of simulations. The first series allows us to obtain the objective function sensitivity to the parameters in the proximity of expected values. The second-one shows the relationships between model parameters versus the objective function value. It was found that with 18 objective functions, it is possible to obtain reliable results of calibration for the model of the-system investigated.

引用

页码：51 / 64

页数：14

共 50 条

[1] Calibration of the activated sludge model with genetic algorithms. Part I. Calibration results
Urban, Rafal
Szetela, Ryszard
[J]. ENVIRONMENT PROTECTION ENGINEERING, 2007, 33 (01): : 31 - 49
[2] On iterative algorithms. II.
Geppert, H
[J]. MATHEMATISCHE ANNALEN, 1933, 108 : 197 - 207
[3] An eco-environmental water demand based model for optimising water resources using hybrid genetic simulated annealing algorithms. Part II. Model application and results
Wang, Xiaoling
Sun, Yuefeng
Song, Lingguang
Mei, Chuanshu
[J]. JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2009, 90 (08) : 2612 - 2619
[4] Intercomparison of in-flight icing algorithms. Part II: Statistical verification results
Brown, BG
Thompson, G
Bruintjes, RT
Bullock, R
Kane, T
[J]. WEATHER AND FORECASTING, 1997, 12 (04) : 890 - 914
[5] Reliability estimation of classification algorithms. II. Integral estimates
Gurov S.I.
[J]. Computational Mathematics and Modeling, 2005, 16 (3) : 279 - 288
[6] An OOP MATLAB Extensible Framework for the Implementation of Genetic Algorithms. Part II: Case Study
Razvan, Cazacu
Lucian, Grama
Ioan, Mocian
[J]. 8TH INTERNATIONAL CONFERENCE INTERDISCIPLINARITY IN ENGINEERING, INTER-ENG 2014, 2015, 19 : 201 - 206
[7] Genetic algorithms for the application of Activated Sludge Model No. 1
Kim, S
Lee, H
Kim, J
Kim, C
Ko, J
Woo, H
Kim, S
[J]. WATER SCIENCE AND TECHNOLOGY, 2002, 45 (4-5) : 405 - 411
[8] Optimization of multistage vapour compression systems using genetic algorithms. Part 2: Application of genetic algorithm and results
West, AC
Sherif, SA
[J]. INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2001, 25 (09) : 813 - 824
[9] PROBLEM-ADAPTIVE NUMERICAL ANALYSIS OF ELECTRONIC CIRCUITS. II. BIDIRECTIONAL ALGORITHMS.
Sigorskii, V.P.
Kolyada, Yu.V.
Kolodnitskii, N.M.
[J]. Radioelectronics and Communications Systems (English translation of Izvestiya Vysshikh Uchebnykh Z, 1987, 30 (06): : 38 - 42
[10] Reliability estimation of classification algorithms. II. Point Bayesian estimates
Gurov S.I.
[J]. Computational Mathematics and Modeling, 2005, 16 (2) : 169 - 178

← 1 2 3 4 5 →