Conjoint approach of the "residual" prediction and the nonlinear autoregressive neural network increases the forecast precision of the base model | Zendy

Alexander Sergeev | Zendy; Andrey Shichkin | Zendy; Alexander Buevich | Zendy; Elena Baglaeva | Zendy; Irina Subbotina | Zendy; Anna Rakhmatova | Zendy; Alexandra I. Kosachenko | Zendy; Anastasia Moskaleva | Zendy; Alexander Medvedev | Zendy; Marina Sergeeva | Zendy

Open Access

Conjoint approach of the "residual" prediction and the nonlinear autoregressive neural network increases the forecast precision of the base model

Author(s) -

Alexander Sergeev,

Andrey Shichkin,

Alexander Buevich,

Elena Baglaeva,

Irina Subbotina,

Anna Rakhmatova,

Alexandra I. Kosachenko,

Anastasia Moskaleva,

Alexander Medvedev,

Marina Sergeeva

Publication year - 2020

Publication title -

aip conference proceedings

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.177

H-Index - 75

eISSN - 1551-7616

pISSN - 0094-243X

DOI - 10.1063/5.0027179

Subject(s) - mean squared error , nonlinear autoregressive exogenous model , autoregressive model , residual , artificial neural network , mean absolute error , nonlinear system , root mean square , statistics , mathematics , computer science , algorithm , artificial intelligence , engineering , physics , quantum mechanics , electrical engineering

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