Self-adjusted multi-sensor information fusion electric energy measuring based on neural networks
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..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2017 |
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| Erschienen: |
2017 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:139, p 00081 |
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| Enthalten in: |
MATEC Web of Conferences - 139, p 00081(2017) |
| Sprache: |
Englisch ; Französisch |
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| Beteiligte Personen: |
Li ZhuFeng [VerfasserIn] |
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| Links: |
doi.org [kostenfrei] |
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| Themen: |
DSP |
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| doi: |
10.1051/matecconf/201713900081 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
DOAJ00509075X |
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| 520 | |a 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. | ||
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