| 基于离散PSO算法的Claus硫磺回收过程模型变量的选择 |
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| 引用本文： | 刘对,李丽娟,张湜. 基于离散PSO算法的Claus硫磺回收过程模型变量的选择[J]. 计算机与应用化学, 2012, 0(7): 863-866 |
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| 作者姓名： | 刘对 李丽娟 张湜 |
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| 作者单位： | 南京工业大学自动化与电气工程学院 |
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| 基金项目： | 江苏省高校自然科学基金(09KJB510003) |
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| 摘 要： | 克劳斯(Claus)硫磺回收过程中存在诸多影响质量指标的变量,利用全部变量建模会增加模型复杂性,且获取的冗余信息会降低建模精度。针对这个问题,本文提出采用基于离散粒子群的算法(PSO)进行建模变量的选择。首先,采用离散PSO算法,通过迭代优化得到建模的最优输入变量组合,再通过偏最小二乘(PLS)对所选变量建立建模。结果:表明,该方法:通过更少的建模变量获得更高的模型精度。
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| 关 键 词： | 硫磺回收 克劳斯工艺 离散粒子群优化算法 变量选择 部分最小二乘法 |
Selection of modeling variables based on discrete PSO in process of Claus sulfur recovery |
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| Liu Dui,Li Lijuan and Zhang. Selection of modeling variables based on discrete PSO in process of Claus sulfur recovery[J]. Computers and Applied Chemistry, 2012, 0(7): 863-866 |
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| Authors: | Liu Dui Li Lijuan Zhang |
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| Affiliation: | Shi (College of Automation and Electrical Engineering,Nanjing University of Technology,Nanjing,211816,Jiangsu,China) |
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| Abstract: | In Claus sulfur recovery process,the quality index are influenced by many variables.Too many variables will result in complication of model structure.Moreover,redundant information will reduce the model accuracy.To solve the problem,an input-selecting algorithm based on discrete PSO(particle swarm optimization algorithm) is presented in this paper.Optimal input variable combination of the Claus sulfur recovery process is obtained by discrete PSO algorithm.Then the model is set up based on the selected variables by PLS algorithm.The simulated results show that higher accuracy is obtained with less modeling variables. |
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| Keywords: | sulfur recovery Claus process discrete PSO variable selection PLS |
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