| 基于改进PSO算法和集成神经网络的裂解炉在线优化 |
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| 引用本文： | 庄敏慧,张照娟,王振雷,钱锋.基于改进PSO算法和集成神经网络的裂解炉在线优化[J].华东理工大学学报(自然科学版),2009,35(5). |
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| 作者姓名： | 庄敏慧 张照娟 王振雷 钱锋 |
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| 作者单位： | 华东理工大学化学工程联合国家重点实验室,上海,200237 |
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| 基金项目： | 国家杰出青年科学基金(60625302);;高等学校学科创新引智计划资助(B08021);;国家973项目(2009CB320603);;国家863计划课题(2006AA04Z168,2007AA041402);;长江学者和创新团队发展计划资助(IRT0721);;国家科技支撑计划(2007BAF22B05);;上海市科技攻关项目(08DZ1123100);;上海市重点学科建设项目资助(B504);;上海市科技启明星计划(07QA14015) |
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| 摘 要： | 针对传统粒子群算法(PSO)寻优时易陷入局部最优、后期全局搜索能力下降等不足,提出了基于载波的粒子群算(CWPSO).通过粒子基于载波的搜索和载波扩展精确寻优,较好地克服了上述缺点,且寻优时间明显减少.同时,针对工业裂解炉在线优化要求,采用了权值动态集成的集成神经网络(NNE)对双烯收率进行建模预测,并结合CWPSO算法进行了在线滚动优化.仿真结果表明,该方法对裂解炉的优化效果明显,双烯平均收率有了明显提高.
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| 关 键 词： | CWPSO 集成神经网络 在线优化 |
Online Optimization of Cracking Furnace Based on Advanced PSO Algorithm and Neural Network Ensembles |
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| ZHUANG Min-hui,ZHANG Zhao-juan,WANG Zhen-lei,QIAN Feng.Online Optimization of Cracking Furnace Based on Advanced PSO Algorithm and Neural Network Ensembles[J].Journal of East China University of Science and Technology,2009,35(5). |
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| Authors: | ZHUANG Min-hui ZHANG Zhao-juan WANG Zhen-lei QIAN Feng |
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| Institution: | State Key Laboratory of Chemical Engineering;East China University ofScience and Technology;Shanghai 200237;China |
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| Abstract: | The traditional Particle Swarm Optimization(PSO) algorithm is easily trapped in the local optimum and converges slowly.Due to the shortcomings above,a novel PSO algorithm based on the carrier-wave(CWPSO) is presented in the paper,which searches through the carrier-wave and takes a precise search by means of carrier-wave extending.As a result,it overcomes the above shortcomings better,and has a shorter searching time as well.In addition,towards the online optimal requirements of the industrial cracking furna... |
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| Keywords: | CWPSO neural network ensembles online optimization |
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