Semi-empirical Neural Network Based Approach to Modelling and Simulation of Controlled Dynamical Systems

被引：8

作者：

Egorchev, Mikhail, V ^{[1
]}

Tiumentsev, Yury, V ^{[1
]}

机构：

[1] Natl Res Univ, Moscow Aviat Inst, Moscow, Russia

来源：

8TH ANNUAL INTERNATIONAL CONFERENCE ON BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES, BICA 2017 (EIGHTH ANNUAL MEETING OF THE BICA SOCIETY) | 2018年 / 123卷

关键词：

nonlinear dynamical system; semi-empirical model; neural network; sequential learning;

D O I：

10.1016/j.procs.2018.01.022

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A modelling and simulation approach is discussed for nonlinear controlled dynamical systems under multiple and diverse uncertainties. The main goal is to demonstrate capabilities for semi-empirical neural network based models combining theoretical domain-specific knowledge with training tools of artificial neural network field. Training of the dynamical neural network model for multi-step ahead prediction is performed in a sequential fashion. Computational experiments are carried out to confirm efficiency of the proposed approach. (C) 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/) Peer-review under responsibility of the scientific committee of the 8th Annual International Conference on Biologically Inspired Cognitive Architectures

引用

页码：134 / 139

页数：6

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