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Application of machine training methods to design of new inorganic compoundsстатья
Информация о цитировании статьи получена из
Scopus
Дата последнего поиска статьи во внешних источниках: 8 января 2017 г.
- Авторы: Kiselyova N., Stolyarenko A., Ryazanov V., Sen'ko O., Dokukin A.
- Сборник: DIAGNOSTIC TEST APPROACHES TO MACHINE LEARNING AND COMMONSENSE REASONING SYSTEMS
- Год издания: 2012
- Издательство: IGI Global
- Местоположение издательства: Hershey, PA, United States
- Первая страница: 197
- Последняя страница: 220
- DOI: 10.4018/978-1-4666-1900-5.ch009
- Аннотация: The review of applications of machine training methods to inorganic chemistry and materials science is presented. The possibility of searching for classification regularities in large arrays of chemical information with the use of precedent-based recognition methods is discussed. The system for computer-assisted design of inorganic compounds, with an integrated complex of databases for the properties of inorganic substances and materials, a subsystem for the analysis of data, based on computer training (including symbolic pattern recognition methods), a knowledge base, a predictions base, and a managing subsystem, has been developed. In many instances, the employment of the developed system makes it possible to predict new inorganic compounds and estimate various properties of those without experimental synthesis. The results of application of this information-analytical system to the computer-assisted design of inorganic compounds promising for the search for new materials for electronics are presented.
- Добавил в систему: Врагова Елена Юрьевна