Data Fitting Method of Customer Electric Energy Consumption Based on Orthogonal Polynomial Neural Network-Reference-Cited by-同舟云学术

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Data Fitting Method of Customer Electric Energy Consumption Based on Orthogonal Polynomial Neural Network

Published:2023-05-12 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 6th International Electrical and Energy Conference (CIEEC)
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Author:

Yu Hong¹,Chen Xi¹,Zhang Letian¹,Wei Lin²,Yang Linlin³,Wang Zixu³

Affiliation:

1. State Grid Jinan Power Supply Company,Jinan,China

2. Shandong University,Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education,Jinan,China

3. State Grid Shandong Electric Power Company Marketing Service Center (Metrology Center), State Grid Shandong Electric Power Company,Jinan,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10165685/10164836/10165881.pdf?arnumber=10165881

Reference16 articles.

1. Designing optimal models of nonlinear MIMO systems based on orthogonal polynomial neural networks

2. Short - term load forecasting of multi - scale recurrent neural networks based on residual structure;zhao;Concurrency and Computation Practice and Experience,2022

3. A comprehensive experimental evaluation of orthogonal polynomial expanded random vector functional link neural networks for regression

4. Neural network interpolation operators optimized by Lagrange polynomial

5. Ultra-short term power load forecasting based on CEEMDAN-SE and LSTM neural network

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