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Self-adjusted multi-sensor information fusion electric energy measuring based on neural networks

机译:基于神经网络的自调整多传感器信息融合电能测量

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摘要

In this article, self-adjusted Multi-sensor Information Fusion measuring method of electric energy based on neural networks has been thoroughly given. This paper studies the method of automatic error correction of electric power measurement also. The effective learning algorithm of the neural network based on gradient algorithm and Newton algorithm is combined with the LEA discriminant method.The results show that the method can improve the learning efficiency. The hardware model of adaptive real-time fast power measurement is constructed by using DSP device. The experimental results show that the adaptive power measurement model is better than the traditional power meter.
机译:在本文中,已经彻底地彻底地提供了基于神经网络的电能的自调整多传感器信息融合测量方法。本文还研究了电力测量的自动纠错方法。基于梯度算法和牛顿算法的神经网络有效学习算法与LEA判别方法相结合。结果表明该方法可以提高学习效率。通过使用DSP设备构建自适应实时快速功率测量的硬件模型。实验结果表明,自适应功率测量模型优于传统功率计。

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