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中文摘要：
提出并研究一种新的神经网络模型——嵌套神经网络模型。将嵌套神经网络模型与BP神经网络相结合,实现模式识别与函数拟合一体化,具体化为嵌套BP神经网络,并用于油气产能预测。实例验证结果表明,嵌套BP神经网络与BP神经网络相比较具有收敛速度快、预测精度高、结果有效性高并具有并行运算的特点,为处理现代化的海量数据提供了构架体系结构。
英文摘要：
This paper proposes and studies a new neural network model — the nested neural network model.Combined the nested neural network model with BP neural network,it achieves the integration of pattern recognition and function fitting,and specifies it into the nested BP neural network,and applies it to the oil and gas production forecast.The results of examples show that compared to BP neural network,the nested BP neural network has faster convergence,higher accuracy and more efficiency,with the characteristics of parallel computing,and provides a framework for dealing with modern massive data.The work explores a new way for the study of the neural network from a single functional module to combination nest.
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