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Research on complex dynamic systems using neural networks

机译:基于神经网络的复杂动力系统研究

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Artificial neural network is a theory and technology developing speedily in intelligence research area of computer in recent years, which is applied in modeling of computer system simulation due to no need of establishing precise physical model and mathematical model in advance. Neural network is a modeling method of system simulation that has strong application. Meanwhile, this method has the capability to acquire knowledge by learning from environment (namely, obtain the law contained in the internal of system by learning from typical sample data of input/output of system), so it has better application for system simulation. Focusing on some actual problems of dynamic system simulation, artificial neural network model and learning algorithm that applies in complex dynamic system modeling are researched in this paper.
机译:人工神经网络是近年来计算机智能研究领域中发展迅速的一种理论和技术,由于不需要事先建立精确的物理模型和数学模型,因此被应用在计算机系统仿真的建模中。神经网络是一种具有较强应用前景的系统仿真建模方法。同时,该方法具有通过从环境中学习来获取知识的能力(即通过从系统的输入/输出的典型样本数据中学习来获得系统内部所包含的规律),因此在系统仿真中具有更好的应用。针对动态系统仿真的一些实际问题,研究了适用于复杂动态系统建模的人工神经网络模型和学习算法。

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