改进的系统云灰色神经网络模型

2008 Second International Conference on Genetic and Evolutionary Computing Pub Date : 2008-10-03 DOI:10.1109/WGEC.2008.62

Sikun Yang

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引用次数: 2

摘要

本文对系统云灰色神经网络模型(SCGNNM(1,1))的拓扑结构进行了改进和优化，提出了一种基于时间响应模型的新型SCGNNM(1,1)。由于时间响应模型的离散数据可以看作是从连续函数中抽象出来的数据，因此可以大大提高模型的精度。同时，给出了学习算法。最后对该模型进行了仿真，结果表明该模型是可靠的。

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An Improved System Cloud Grey Neural Network Model

This paper improved and optimized the topology structure of the system cloud grey neural network model (SCGNNM (1,1)) and presented a novel SCGNNM (1,1) based on time response model. Because the dispersed data of time response model can be regarded as the data abstracted from the continued function, the model's precision can be improved greatly. Meantime, the learning algorithm is given. Finally, the proposed model is simulated and shown to be very reliable.

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2008 Second International Conference on Genetic and Evolutionary Computing

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