Construction of an analytical method for limiting the complexity of neural-fuzzy models with guaranteed accuracy
Journal Title: Восточно-Европейский журнал передовых технологий - Year 2019, Vol 2, Issue 4
Abstract
<p>We have proposed an analytical method for limiting the complexity of neural-fuzzy models that provide for the guaranteed accuracy of their implementation when approximating functions with two or more derivatives. The method makes it possible to determine the required minimal number of parameters for systems that employ fuzzy logic, as well as neural models.</p><p>We have estimated the required number of neurons (terms) in a model, which ensure the accuracy required for the area of a model curve to approach the system one along the sections of function approximation. The estimate for an approximation error was obtained based on the residual members of decomposition, in the Lagrangian form, of areas of the approximated system function into a Maclaurin series. The results received make it possible to determine the required number of approximation sections and the number of neurons (terms) in order to ensure the assigned relative and absolute error of approximation.</p><p>We have estimated the required number of neurons (terms) that provide for the necessary accuracy of model implementation based on the maximum deviation between the system and model curves along the section of approximation. This makes it possible to select, depending on the assigned required accuracy, the number of terms of fuzzy variables, input and output variables, linguistic rules, coordinates of modal values along the axes of input and output variables.</p><p>To verify validity of the proposed solutions, we modeled the system curves in the Matlab/Simulink environment, which confirmed the guaranteed accuracy of their implementation in accordance with the analytical calculations reported earlier.</p>The results obtained could be applied in modern intelligent technical systems of management, control, diagnosis, and decision-making. Using the proposed methods for selecting and applying the minimal number of terms (neurons) would help reduce the required computing power in nonlinear systems
Authors and Affiliations
Borys Sytnik, Volodymyr Bryksin, Sergiy Yatsko, Yaroslav Vashchenko
Keywords
Related Articles
- EP ID EP666295
- DOI 10.15587/1729-4061.2019.160719
- Views 76
- Downloads 0
The results of study into the effect of airsteam blast on the lowgrade fuel gasification process
<p class="a">The design of a highly efficient gas generating plant with a directflow gas generator was proposed for gasification of lowgrade fuels. The design includes a gasair recuperator and an evaporator for prelim...
Experimental study of the fluctuations of gas medium parameters as early signs of fire
<p>The results of the experimental study of fluctuations of dynamics of hazardous factors of gaseous medium at early ignition of combustible materials in the chamber, simulating pressurized premises, are presented. The a...
CFD modelling of particle size effect on stoker coalfired boilers combustion
<p>In the previous study, CFD simulation had been developed to predict combustion characteristic on the Fluidized Bed Boiler and Pulverized Boiler. The high demand on coal used for stoker-fired boilers in Indonesia the p...
Efficiency analysis of the technology of roller formation of finely-grained concrete products
<p><span style="font-family: 'Times New Roman'; font-size: small;">Efficiency of using the roller forming technology with forced rotation of the working body (roller or sector) was disclosed. The results of development o...
Study of the lamb waves propagation along a plate in contact with a randomly inhomogeneous heterogeneous medium
<p>We present results of research into the influence of characteristics of a heterogeneous medium on the Lamb wave propagation process parameters along a plate in contact with a given medium. A mathematical description o...