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pso optimize algorithm
相关语句
  粒子群优化算法
     Research on PSO Optimize Algorithm Based on Path of Moving Object
     基于运动目标路径的粒子群优化算法研究
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  相似匹配句对
     Meanwhile,PSO is introduced to optimize the parameters of Laplace wavelet.
     同时为了提高识别效率,引入了粒子群算法来实现Laplace小波的参数寻优.
短句来源
     A PSO Based Approach to Optimize PID Parameters
     基于粒子群算法的PID参数优化
短句来源
     The PSO is a evolutional algorithm and a preferable optimize method.
     粒子群优化(PSO)算法是一种进化算法是一种较好的优化方法。
短句来源
     to optimize the structure;
     优化结构 ,增加供给有效性 ;
短句来源
     How to optimize G.
     G.
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Aim GA-PSO, an optimize algorithm which is superior to pure GP is given.Methods Through changing the question′s description of hierarchy into the fix length linear structure, making GP and GA come to an unification. In addition, a new operator is introduced and applied to add PSO into GA frame, which forms the GA-PSO programming.Results From the description of the solving to the genetic operators, PSO operators and the construction of GA-PSO frame, a integrated GA-PSO...

Aim GA-PSO, an optimize algorithm which is superior to pure GP is given.Methods Through changing the question′s description of hierarchy into the fix length linear structure, making GP and GA come to an unification. In addition, a new operator is introduced and applied to add PSO into GA frame, which forms the GA-PSO programming.Results From the description of the solving to the genetic operators, PSO operators and the construction of GA-PSO frame, a integrated GA-PSO programming is presented.Conclusion GA-PSO optimize algorithm is superior to pure GP and GA. It is a good optimization method with strong competitiveness.

目的 提出一个比GP算法更优的GA-PSO混合的规划算法。方法 通过将层次型问题的描述转换为固定长度线形结构的描述方式,使GP算法与GA规划算法达到统一;通过构造运算符,将PSO算法引入到GA规划算法框架之中,形成GA-PSO混合规划算法。结果 从解的描述、遗传算子、PSO运算符的构造再到GA-PSO算法框架,提出了完整的GA-PSO混合规划算法。结论 实证研究显示,GA-PSO混合规划算法优于GP算法以及GA算法。

The paper is meant to set up a enterprise credit risk evaluation model by a new AI method—GA-PSO optimize algorithm.We tested the model by using the data of so companies of the stock Market of Shanghai.The result shows that this model can predict the listed companies credit risk effectively.It is superior to traditional Multiple Regression's calculating model and GP in model′s astringency and predict accuracy.

利用一种新的人工智能方法———GA-PSO混合规划算法构建企业信用风险评估模型。并利用上证50若干企业的实际数据对模型进行了实证检验。实证结果显示该模型能有效预测上市企业的信用风险状况。该模型在收敛性能及预测准确率等方面优于基于传统的多元回归方法及GP方法的信用风险评估模型。

 
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