自组织建模方法及西部GDP增长模型研究

Self Organizing Methods and a Model Study on the Growth of West China's GDP

在自组织控制理论的基础上 ,引入人工神经网络思想提出一种新的数据挖掘方法。建模过程中活动神经元逐层大量产生和淘汰 ,模型得以最终进化到其最优复杂性。阐述了自组织算法原理、建模步骤及网络结构。给出针对西部地区经济发展的建模研究实例 ,以确定西部开发中最重要的若干因素 ,并量化分析各自力度强弱。比较全国模型得到西部经济特点 。

On the basis of the theory of self organizing cybernetics, a new data mining method is proposed by using the principles of artificial neural networks. During modeling, active neurons are generated and eliminated largely, enabling the model to evolve into its optimal complex. Some principles, processes and network structures of self-organization method are discussed. As an example, the economy in the west China is studied with the model to find the critical factors. Some suggestions about the development of the west China are put forward.