一种RBF神经网络的混合学习算法在CPI中的应用OA
An Optimized Hybrid Algorithm of RBF Neural Networks Model in CPI Forecasting
根据RBF神经网络最常用的OLS算法、K-均值聚类算法和梯度下降训练学习算法,提出了一种基于正交最小二乘K-均值聚类梯度下降优化的RBF神经网络的混合算法.该算法克服了单一某种训练方法的不足,发挥了混合算法的长处,进行了CPI预测的仿真实验.结果证明:该方法是有效实用.
This paper proposes an optimized Hybrid algorithm based on K-means clustering, orthogonal least squares (OLS) and Gradient descent algorithm. By applying K-means clustering and OLS algorithm to train the central position and width of the basis function adopted in the RBFNN, and computing the network's weights with least-squaremethod,In addition,by combining the gradient algorithm,via minimizing the objective function to adjust the data center and width of th…查看全部>>
罗芳琼
柳州师范高等专科学校数学与计算机科学系 柳州 545004
信息技术与安全科学
RBF神经网络优化混合算法CPI预测
RBF neural network optimized hybrid algorithm CPI forecasting
《计算机与数字工程》 2012 (4)
8-11,4
柳州师范高等专科学校科研项目(编号:LSZ2011B007).
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