| Форма представления | Статьи в зарубежных журналах и сборниках |
| Год публикации | 2019 |
| Язык | английский |
|
Медведева Ольга Анатолиевна, автор
|
| Библиографическое описание на языке оригинала |
Medvedeva Olga Anatolievna, Ivanov Aleksandr Nikolaevich, Morozkin Nikolay Danilovich, Svetlana Anatol'evna Mustafina. NEURAL NETWORKS WITH PSEUDO-RANDOM DISTRIBUTION OF RELATIONSHIPS USING THE EXAMPLE OF MERCURY ELECTROLYZER OPERATION MODE MODELING // INTERNATIONAL TRANSACTION JOURNAL OF ENGINEERING MANAGEMENT & APPLIED SCIENCES & TECHNOLOGIES. - 2019. - Vol.10, Is.16. - Art. №10A16A. |
| Аннотация |
This article analyzed the applicability of artificial neural networks to
solve the problems of physicochemical process modeling using the
example of the mercury electrolyzer operation mode used in caustic soda
production. This paper also described the basic qualities of the existing
neural networks and the ways of their training. The authors propose the
solution to the problem of modeling based on the networks with
pseudo-random distribution of connections. This paper described the
architecture of these networks, three learning algorithms are proposed.
The implementation of neural networks with pseudo-random distribution
of connections was performed by Python programming language. The
article presents the comparative learning results of different networks
with different sets of hyperparameters. Also, the determination of the
optimal settings of neural networks allows achieving high learning
efficiency. The resulting neural network model described the
electrolysis process adequately in accordance with the available source
data. |
| Ключевые слова |
Neural networks Modeling, Machine learning, Hyperparameters,
Electrolysis, Pseudorandom distribution of connections. |
| Название журнала |
INTERNATIONAL TRANSACTION JOURNAL OF ENGINEERING MANAGEMENT & APPLIED SCIENCES & TECHNOLOGIES
|
| URL |
http://tuengr.com/V10A/10A16A.pdf |
| Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на эту карточку |
https://repository.kpfu.ru/?p_id=216273 |
Полная запись метаданных  |
| Поле DC |
Значение |
Язык |
| dc.contributor.author |
Медведева Ольга Анатолиевна |
ru_RU |
| dc.date.accessioned |
2019-01-01T00:00:00Z |
ru_RU |
| dc.date.available |
2019-01-01T00:00:00Z |
ru_RU |
| dc.date.issued |
2019 |
ru_RU |
| dc.identifier.citation |
Medvedeva Olga Anatolievna, Ivanov Aleksandr Nikolaevich, Morozkin Nikolay Danilovich, Svetlana Anatol'evna Mustafina. NEURAL NETWORKS WITH PSEUDO-RANDOM DISTRIBUTION OF RELATIONSHIPS USING THE EXAMPLE OF MERCURY ELECTROLYZER OPERATION MODE MODELING // INTERNATIONAL TRANSACTION JOURNAL OF ENGINEERING MANAGEMENT & APPLIED SCIENCES & TECHNOLOGIES. - 2019. - Vol.10, Is.16. - Art. №10A16A. |
ru_RU |
| dc.identifier.uri |
https://repository.kpfu.ru/?p_id=216273 |
ru_RU |
| dc.description.abstract |
INTERNATIONAL TRANSACTION JOURNAL OF ENGINEERING MANAGEMENT & APPLIED SCIENCES & TECHNOLOGIES |
ru_RU |
| dc.description.abstract |
This article analyzed the applicability of artificial neural networks to
solve the problems of physicochemical process modeling using the
example of the mercury electrolyzer operation mode used in caustic soda
production. This paper also described the basic qualities of the existing
neural networks and the ways of their training. The authors propose the
solution to the problem of modeling based on the networks with
pseudo-random distribution of connections. This paper described the
architecture of these networks, three learning algorithms are proposed.
The implementation of neural networks with pseudo-random distribution
of connections was performed by Python programming language. The
article presents the comparative learning results of different networks
with different sets of hyperparameters. Also, the determination of the
optimal settings of neural networks allows achieving high learning
efficiency. The resulting neural network model described the
electrolysis process adequately in accordance with the available source
data. |
ru_RU |
| dc.language.iso |
ru |
ru_RU |
| dc.subject |
Neural networks Modeling |
ru_RU |
| dc.subject |
Machine learning |
ru_RU |
| dc.subject |
Hyperparameters |
ru_RU |
| dc.subject |
Electrolysis |
ru_RU |
| dc.subject |
Pseudorandom distribution of connections. |
ru_RU |
| dc.title |
NEURAL NETWORKS WITH PSEUDO-RANDOM DISTRIBUTION OF RELATIONSHIPS USING THE EXAMPLE OF MERCURY ELECTROLYZER OPERATION MODE MODELING |
ru_RU |
| dc.type |
Статьи в зарубежных журналах и сборниках |
ru_RU |
|
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