| 模糊粒子群神经网络算法及应用 |
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| 引用本文： | 李澄非,朱群雄.模糊粒子群神经网络算法及应用[J].计算机与应用化学,2007,24(10):1359-1362. |
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| 作者姓名： | 李澄非 朱群雄 |
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| 作者单位： | 北京化工大学信息科学与技术学院，北京化工大学信息科学与技术学院 北京，100029，北京，100029 |
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| 基金项目： | 中国石油化工股份有限公司资助项目 |
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| 摘 要： | 针对流程工业神经网络建模时,BP算法的局部收敛问题,采用模糊粒子群算法改进神经网络学习问题。该算法将模糊粒子群引入神经网络学习算法,使得粒子群的权重自适应更新,同时模糊粒子群自适应调整神经网络权重参数,改进网络收敛性。将算法用于建立乙烯裂解炉出口温度(COT)、裂解产品收率软测量模型,取得了较好的应用效果。
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| 关 键 词： | 模糊粒子群 神经网络 乙烯裂解 |
| 文章编号： | 1001-4160（2007）10-1359-1362 |
| 修稿时间： | 2007-01-22 |
Fuzzy particle swarm artificial neural network and its application |
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| Li Chengfei,Zhu Qunxiong.Fuzzy particle swarm artificial neural network and its application[J].Computers and Applied Chemistry,2007,24(10):1359-1362. |
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| Authors: | Li Chengfei Zhu Qunxiong |
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| Affiliation: | School of Information Science and Technology, Beijing University of Chemical Technology, Bejing, 100029, China |
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| Abstract: | The fuzzy Particle Swarm Optimization(PSO) and Artificial Neural Network model are proposed to improve BP-ANN convergence speed and stability. The proposed approach is applied successfully to handle the predication and optimization of cracking model. From both theoretical computing and practical application, the validity and reliability of proposed algorithm are verified by two case studies , namely the foundation of the soft measurement model of the coil outlet temperature, the yields of ethylene and propylene. |
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| Keywords: | fuzzy particle swarm artificial neural network ethylene cracking |
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