Identification of Dynamical System’s Parameters using Neural Networks

dc.contributor.author	Kushnir, Dmytro
dc.date.accessioned	2024-02-14T16:56:25Z
dc.date.available	2024-02-14T16:56:25Z
dc.date.issued	2019
dc.identifier.citation	Kushnir, Dmytro. Identification of Dynamical System’s Parameters using Neural Networks / Kushnir, Dmytro; Supervisor: Lyubomyr Demkiv; Ukrainian Catholic University, Department of Computer Sciences. – Lviv: 2019. – 61 p.	uk
dc.identifier.uri	https://er.ucu.edu.ua/handle/1/4484
dc.language.iso	en	uk
dc.title	Identification of Dynamical System’s Parameters using Neural Networks	uk
dc.type	Preprint	uk
dc.status	Публікується вперше	uk
dc.description.abstracten	Parameter identification of Dynamical systems examined in the context of its value for the DNN training process facilitation and mitigation of the data imbalance. In the result of the theoretical analysis of the stated problem’s methodological roots, were proposed the approach of augmenting usual NN model with part responsible for explicit representation of required parameters. Moreover, this approach involves the change of a learning procedure towards indirect supervision setting, where the NN responsible for system modeling, in form of time series prediction, does not ob- serves the dataset at all but is being taught via the intermediate step of identification of target system parameter knowing its physical interpretation. Work considered the dynamical process on the example of DC motor described by the system of the ordinary nonlinear differential equations.	uk