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Time-series trend estimating system and method using column- structured recurrent neural network
Time-series trend estimating system and method using column- structured recurrent neural network
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机译：使用列结构递归神经网络的时间序列趋势估计系统和方法
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摘要
Each neural element of a column-structured recurrent neural network generates an output from input data and recurrent data provided from a context layer of a corresponding column. One or more candidates for an estimated value is obtained, and an occurrence probability is computed using an internal state by solving an estimation equation determined by the internal state output from the neural network. A candidate having the highest occurrence probability is an estimated value for unknown data. Thus, the internal state of the recurrent neural network is explicitly associated with the estimated value for data, and a data change can be efficiently estimated.
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