APPLICATION OF CLOUD-BASED SPREADSHEETS TO ARTIFICIAL NEURAL NETWORK MODELLING

Oksana Markova, Serhiy Semerikov

Abstract


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.


Keywords


Anderson’s Iris; computer simulation; neural networks; cloud-based spreadsheets

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References


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DOI: http://dx.doi.org/10.21303/2585-6847.2019.001039

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ISSN 2585-6847 (Online), ISSN 2585-6839 (Print)