[1]吴建生.基于粒子群算法的神经网络短期降水预报建模研究[J].智能系统学报,2006,1(2):67-73.
WU Jian-sheng.Study on the shorttime rainfall prediction model of neural ensemble based on PSO algorithms[J].CAAI Transactions on Intelligent Systems,2006,1(2):67-73.
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WU Jian-sheng.Study on the shorttime rainfall prediction model of neural ensemble based on PSO algorithms[J].CAAI Transactions on Intelligent Systems,2006,1(2):67-73.
基于粒子群算法的神经网络短期降水预报建模研究
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
1
期数:
2006年第2期
页码:
67-73
栏目:
学术论文—机器学习
出版日期:
2006-10-25
- Title:
- Study on the shorttime rainfall prediction model of neural ensemble based on PSO algorithms
- 文章编号:
- 1673-4785(2006)02-0067-07
- 分类号:
- TP183
- 文献标志码:
- A
- 摘要:
- 用多样性粒子群算法优化神经网络的网络结构和连接权，获得神经网络集成个体；进一步用二次规划方法，计算各集成个体的最优非负权系数进行组合集成，生成神经网络集成的输出结论，进行短期降水预报建模研究.以广西全区的月降水量实例分析，结果表明该方法能有效提高系统的泛化能力.
- Abstract:
- This paper presents the evolving neural network architecture and connection weig hts based on Diversityguided Particle Swarm Optimization algorithms. The ensem ble strategy is carried out by using the quadratic programming to calculate the best nonnegative weights. The weighted coefficient of each ensemble individual is o b tained. This method can be used to establish the forecast model of the shortti m e rainfall. The applied example is built with the monthly mean rainfall in the w hole area of Guangxi. The result shows that this method can effectively increase the generalization ability of neural network.
- 参考文献/References:
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备注/Memo
收稿日期：2006-04-28.
基金项目：广西省教育厅资助项目(200508234)
作者简介：
吴建生，男，1974年生，硕士，讲师，主要研究方向为神经网络应用及智能优化算法研究
.E-mail: wjsh2002168@163.com.
更新日期/Last Update:
2009-05-05