Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (24): 37-39.DOI: 10.3778/j.issn.1002-8331.2010.24.011

• 研究、探讨 • Previous Articles     Next Articles

Novel neural network learning algorithm for solving quadratic programming with linear constraints

YAGN Jing-li,DU Ting-song   

  1. Institute of Nonlinear and Complex Systems,China Three Gorges University,Yichang,Hubei 443002,China
  • Received:2009-11-23 Revised:2010-03-29 Online:2010-08-21 Published:2010-08-21
  • Contact: YAGN Jing-li



  1. 三峡大学 非线性与复杂系统研究所,湖北 宜昌 443002
  • 通讯作者: 杨静俐

Abstract: A novel neural network algorithm is proposed,which solves the quadratic programming problem with linear constraints based on 0.618 method.Compared with the existing models for solving the quadratic programming problem with linear constraints,it is more universal and has higher accuracy.Finally,examples are provided to show the applicability of the proposed neural network algorithm.

Key words: quadratic programming, 0.618 method, neural network, learning algorithm

摘要: 提出了一种基于0.618法求解具有线性约束的二次规划问题的神经网络学习新算法。与已有的求解线性约束的二次规划问题的神经网络学习算法相比,该算法的适用范围更广,计算精度更高。其目的是为具有线性约束的二次规划问题的求解提供一种新方法。仿真实验验证了新算法的有效性。

关键词: 二次规划, 0.618法, 神经网络, 学习算法

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