欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
在径向基神经网络学习算法的基础上，提出了一种新的RBF神经网络学习算法，该算法将变长度染色体遗传算法和最小二乘法相结合，能够同时确定径向基神经网络的结构和参数。用此方法建立热电厂热负荷预测模型，并与BP神经网络和增长型结构学习算法的RBF神经网络方法相比较，结果表明可以取得更好的效果。
英文摘要：
Based on the study of radial basis function （RBF） neural network training algorithm, a new RBF neural network training algorithm was introduced by combining genetic algorithm of chromosomes with changeable length and least--square method. It is able to determine the structure and parameters of network. The new training algorithm was used to model heat loading forecasting for co--generation power plants, compares with BP neural network and RBF neural network based on a training algorithm of automatic increase in hidden nodes. Simulation results show that the proposed method is valid.
同期刊论文项目
同项目期刊论文
Passive Stability and Synchronization of Complex Spatio-Temporal Switching Networks with Coupling De
期刊信息
位置：