MODELING METHOD USING COMBINED ARTIFICIAL NEURAL NETWORK
2011 ◽
Vol 10
(02)
◽
pp. 189-198
Keyword(s):
To improve the modeling performance — such as accuracy and robustness — of artificial neural network (ANN), a new combined ANN and corresponding optimal modeling method are proposed in this paper. The combined ANN consists of two parallel sub-networks, and methods such as "early stopping" and "data resampling" are jointly used in training process to reduce the sensitivity of the modeling performance to its structure. To achieve better performance, the structure of combined ANN is proposed to be adjusted dynamically according to the information of expectation error and real error. Simulation experimental results verify that the optimal modeling method using combined ANN can achieve much better performance than the traditional method.
2014 ◽
Vol 17
(1)
◽
pp. 56-74
◽
2022 ◽
2021 ◽
Vol 7
(2)
◽
pp. 149
Application of the Artificial Neural Network (ANN) Method as MPPT Photovoltaic for DC Source Storage
2019 ◽
Vol 12
(3)
◽
pp. 145
◽
2020 ◽
Vol 9
(1.4)
◽
pp. 658-663
2016 ◽
Vol 13
(7)
◽
pp. 652-661