Automatic search of reliability function by symbolic regression

A reliability index of various electronics is determined by the experimental data of tests for different values of parameters of the equipment. The received data are collected in bulky tables and references. This paper presents modern numerical approach, allowing to compile the experimental data on changes of reliability index not in the form of tables but as a function of the operating parameters of the devices. The methodology is based on the method of network operator for the design of the optimal structure of function and selection of its parameters. The network operator method belongs to a class of methods of symbolic regression and provides an evolutionary search for the best compositions of mathematical expressions on the space of elementary structures. The method allows you to automatically receive the required description of the functional dependencies. The effectiveness of the method is demonstrated by the example of searching the law, which describes the change in the failure rate depending on three parameters that characterize its constructive and technological performance and operating conditions. © 2017 IEEE.

Авторы
Diveev A.I. 1 , Sofronova E.A. 2 , Shmalko E.Yu. 1 , Zhadnov V.V.3
Редакторы
-
Издательство
Institute of Electrical and Electronics Engineers Inc.
Номер выпуска
-
Язык
Английский
Страницы
61-66
Статус
Опубликовано
Подразделение
-
Ссылка
-
Номер
-
Том
2017-January
Год
2017
Организации
  • 1 Federal Research Centre “Computer Science and Control” of Russian Academy of Sciences, RUDN University, Moscow, Russian Federation
  • 2 Peoples Friendship University of Russia (RUDN University), Moscow, Russian Federation
  • 3 Moscow Institute of Electronic and Mathematics, National Research University, Higher School of Economics”, Moscow, Russian Federation
Ключевые слова
Electronic engineering; Genetic algorithm; Reliability index; Symbolic regression
Дата создания
19.10.2018
Дата изменения
19.10.2018
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/5189/