 ## Использование адаптивных алгоритмов отбора существенных признаков при нейросетевом решении обратной задачи электроразведкистатья

Статья опубликована в журнале из перечня ВАК
• Авторы:
• Журнал: Нейрокомпьютеры: разработка, применение
• Номер: 3
• Год издания: 2010
• Издательство: Издательство "Радиотехника"
• Местоположение издательства: Москва
• Первая страница: 46
• Последняя страница: 54
• Аннотация: Разработан алгоритм поэтапного отбора существенных признаков и приведены результаты его применения на данных нескольких моделей распределений электропроводности.This study is devoted to development of an algorithm for selection of significant features in neural network based solution of the inverse problem (IP) of magnetotellurics (MT) in geophysics. Solution of such problem is the process of creation of an operator mapping a data vector of the values of electromagnetic field observed on earth surface to the vector of the sought-for geophysical parameters of the section. These parameters include distribution of electrical conductivity in different points of the studied region, geometrical dimensions of separate sub-regions (geological structures) etc. Actual sections are extremely complex and require a very large number of parameters to describe them, thus leading to the known instability (incorrectness) of MT IP. In this study, MT IP was solved with the help of neural networks (NN), namely multilayer perceptions. The dimensionality of 2D MT IP considered in this study is about D=6.5·10I at the input (the dimension of the vector of the observed values) and about D3O=3·10 at the output (dimensionality of the vector describing the distribution of electrical conductivity). To reduce the output dimensionality of a problem, it was divided into D2 problems with one output each. To reduce the input dimensionality, the following methods of significant feature selection (SSF) were used: NN weight analysis (NNWA) and correlation analysis (CA). In this study, a three-step algorithm for IP solution using SSF has been suggested and considered. Two modifications of the algorithm have been considered: the one using NNWA only and the one using CA at one of the steps of the algorithm.O
• Добавил в систему: Шугай Юлия Сергеевна

### Работа с статьей

  Использование адаптивных алгоритмов отбора существенных признаков при нейросетевом решении обратной задачи электроразведки / А. Г. Гужва, С. А. Доленко, Е. А. Оборнев и др. // Нейрокомпьютеры: разработка, применение. — 2010. — № 3. — С. 46–54. Разработан алгоритм поэтапного отбора существенных признаков и приведены результаты его применения на данных нескольких моделей распределений электропроводности.This study is devoted to development of an algorithm for selection of significant features in neural network based solution of the inverse problem (IP) of magnetotellurics (MT) in geophysics. Solution of such problem is the process of creation of an operator mapping a data vector of the values of electromagnetic field observed on earth surface to the vector of the sought-for geophysical parameters of the section. These parameters include distribution of electrical conductivity in different points of the studied region, geometrical dimensions of separate sub-regions (geological structures) etc. Actual sections are extremely complex and require a very large number of parameters to describe them, thus leading to the known instability (incorrectness) of MT IP. In this study, MT IP was solved with the help of neural networks (NN), namely multilayer perceptions. The dimensionality of 2D MT IP considered in this study is about D=6.5·10I at the input (the dimension of the vector of the observed values) and about D3O=3·10 at the output (dimensionality of the vector describing the distribution of electrical conductivity). To reduce the output dimensionality of a problem, it was divided into D2 problems with one output each. To reduce the input dimensionality, the following methods of significant feature selection (SSF) were used: NN weight analysis (NNWA) and correlation analysis (CA). In this study, a three-step algorithm for IP solution using SSF has been suggested and considered. Two modifications of the algorithm have been considered: the one using NNWA only and the one using CA at one of the steps of the algorithm.O.