Будь ласка, використовуйте цей ідентифікатор, щоб цитувати або посилатися на цей матеріал: http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/3566
Назва: Application of cloud-based spreadsheets to artificial neural network modelling
Автори: Маркова, Оксана Миколаївна
Семеріков, Сергій Олексійович
Ключові слова: Anderson’s Iris
computer simulation
neural networks
cloud-based spreadsheets
Дата публікації: 23-лис-2019
Бібліографічний опис: Markova O. M. Application of cloud-based spreadsheets to artificial neural network modelling [Electronic resource] / Oksana Markova, Serhiy Semerikov // Proceedings of the 3rd Annual Conference Technology Transfer: fundamental principles and innovative technical solutions. 23 November 2019. Tallinn, Estonia. – P. 12-15. – DOI : 10.21303/2585-6847.2019.001039. – Access mode : http://eu-jr.eu/ttfpits/article/download/1039/999
Короткий огляд (реферат): The article substantiates the necessity to develop methods of computer simulation of neural networks in the spreadsheet environment. The systematic review of their application to simulating artificial neural networks is performed. The authors distinguish basic approaches to solving the problem of network computer simulation training in the spreadsheet environment, joint application of spreadsheets and tools of neural network simulation, application of third-party add-ins to spreadsheets, development of macros using the embedded languages of spreadsheets; use of standard spreadsheet add-ins for non-linear optimization, creation of neural networks in the spreadsheet environment without add-ins and macros. It is shown that to acquire neural simulation competences in the spreadsheet environment, one should master the models based on the historical and genetic approach. The article considers ways of building neural network models in cloud-based spreadsheets, Google Sheets. The model is based on the problem of classifying multidimensional data provided in “The Use of Multiple Measurements in Taxonomic Problems” by R. A. Fisher. Edgar Anderson’s role in collecting and preparing the data in the 1920s–1930s is discussed as well as some peculiarities of data selection.
Опис: 1. Semerikov, S. O., Teplytskyi, I. O., Yechkalo, Yu. V., Kiv, A. E. (2018) Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot. CEUR Workshop Proceedings, 2257, 122–147. Available at: http://ceur-ws.org/ Vol-2257/paper14.pdf 2. Semerikov, S. O., Teplytskyi, I. O., Yechkalo, Yu. V., Markova, O. M., Soloviev, V. N., Kiv, A. E. (2019). Computer Simulation of Neural Networks Using Spreadsheets: Dr. Anderson, Welcome Back. CEUR Workshop Proceedings, 2393, 833–848. Available at: http://ceur-ws.org/Vol-2393/paper_348.pdf 3. Zaremba, T. (1990). Case Study III: Technology in Search of a Buck. Neural Network PC Tools, 251–283. doi: https://doi.org/ 10.1016/b978-0-12-228640-7.50018-0 4. Hewett, T. T. (1985). Using an Electronic Spreadsheet Simulator to Teach Neural Modeling of Visual Phenomena (Report No. MWPS-F-85-1). Drexel University, Philadelphia. 5. Ruggiero, M. (1993). Pat. No. 5,241,620 US. Embedding neural networks into spreadsheet applications. declareted: 31.08.1993. 6. Kendrick, D. A., Mercado, P. R., Amman, H. M. (2006). Computational Economics. Princeton University Press. doi: https:// doi.org/10.1515/9781400841349 7. Stebbins, G. L. (1978). Edgar Anderson 1897-1969. National Academy of Sciences, Washington. 8. Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7 (2), 179–188. doi: https://doi.org/10.1111/j.1469-1809.1936.tb02137.x 9. Anderson, E. (1935). The irises of the Gaspé Peninsula. Bulletin of the American Iris Society, 59, 2–5. 10. Anderson, E. (1936). The Species Problem in Iris. Annals of the Missouri Botanical Garden, 23 (3), 457. doi: https://doi.org/ 10.2307/2394164
URI (Уніфікований ідентифікатор ресурсу): http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/3566
https://doi.org/10.21303/2585-6847.2019.001039
ISSN: 2585-6847
Розташовується у зібраннях:Кафедра інформатики та прикладної математики

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