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multilayer artificial neural network performance evaluation apparatus including multiple sub models and method therefor

机译:多层人工神经网络性能评估装置,包括多个子模型和方法

摘要

In the artificial neural network modeled based on the physical causal relationship, it is possible to evaluate the performance of the artificial neural network according to the combination of the input variable items and sub-models of each sub-model, and accordingly, provide information on the optimal artificial neural network configuration. It relates to a multilayer artificial neural network performance evaluation apparatus including a plurality of sub-models and a method thereof, wherein each input variable input to a plurality of sub-models is increased or decreased, and an evaluation index is calculated by measuring the output of each sub-model according to the increase or decrease. Its purpose is to evaluate the performance of a multilayer artificial neural network including a plurality of sub-models, and to provide design information of an artificial neural network structure showing optimal reliability according to the evaluation result.
机译:在基于物理因果关系建模的人工神经网络中,可以根据每个子模型的输入可变项目和子模型的组合评估人工神经网络的性能,因此提供了信息最佳的人工神经网络配置。它涉及一种多层人工神经网络性能评估装置,包括多个子模型及其方法,其中输入到多个子模型的每个输入变量增加或减少,并且通过测量输出来计算评估索引每个子模型根据增加或减少。其目的是评估包括多个子模型的多层人工神经网络的性能,并提供根据评估结果的人工神经网络结构的设计信息。

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