Автор:
| Название: | Development of an algorithm for obtaining and analyzing data from regions to assess their development in the context of the transition of industry 4.0 | 
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| Тематика: | экономика | |
| Вид ресурса: | электронное немультимедийное издание | |
| Тип ресурса: | Статья | |
| Целевое назначение: | Научное | |
| Целевая аудитория: | Исследователь | |
| Аннотация: | The transition to Industry 4.0 is accompanied by significant progress and change in many areas of society and the economy. Digitalization changes and improves business processes, simplifies and enriches people's lives. Innovation is taking place. New tools provide, among other things, the collection of large amounts of data. In this regard, the problem of big data analysis is urgent. Since this task is associated with a large amount of digital computing and relies heavily on advanced software and server tools, we were faced with the task of conducting such an in-depth analysis with available software tools with high efficiency. The constructed multi-level universal algorithm for obtaining, collecting, processing and visualizing data is implemented in Microsoft Excel using the Power Pivot add-on. The analysis carried out in the study is aimed at identifying and comparing regions in terms of the level of development of spheres of public life, including the level of digitalization in the context of industry 4.0. | |
| Дата издания: | 2023 | |
| Дата загрузки: | 25.07.2023 | |
| Издательство: | SPIE | |
| Название: | Development of an automated system for searching for profitable investment decision in the argo-industrial complex |
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| Тематика: | экономика | |
| Вид ресурса: | электронное немультимедийное издание | |
| Тип ресурса: | Статья | |
| Целевое назначение: | Научное | |
| Целевая аудитория: | Исследователь | |
| Аннотация: | This article has a practical orientation and is devoted to the development of an automated system that searches for profitable investments. It includes blocks that carry out fundamental analysis, rating assessment of the proposed object for investment, a module for analyzing and forecasting profitability, a module that allows you to assess the possible negative consequences of the total investment portfolio using models of the conditional value of risk and audit risk. The implementation of the methodology included in the developed software was carried out on the example of the agro-industrial complex of the Russian Federation | |
| Дата издания: | 2023 | |
| Дата загрузки: | 25.07.2023 | |
| Издательство: | SPIE | |
| Название: | Models for forecasting indicators based on neural network, regression analysis, and big data |
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| Тематика: | экономика | |
| Вид ресурса: | электронное немультимедийное издание | |
| Тип ресурса: | Статья | |
| Целевое назначение: | Научное | |
| Целевая аудитория: | Исследователь | |
| Аннотация: | The article discusses an approach to the analysis of static information based on the use of neural network technologies and regression models. The forecast for the neural network was made on the basis of official statistics, data on the development of advanced technologies, and also taking into account the current situation in the dynamics of the incidence in Russia for the period from 2003 to 2020. As a result, forecasts for the next 5 years were determined. Growth is expected to continue, but at a slower pace. At this stage, the incidence and the introduction of quarantine measures adversely affect the situation and lead to a reduction in consumption. It is worth noting that the trends in the production of innovative technologies will continue, despite the negative consequences of the pandemic. This is evidenced by forecast data. | |
| Дата издания: | 2023 | |
| Дата загрузки: | 25.07.2023 | |
| Издательство: | SPIE | |
| Название: | Computer and information technologies in the agro-industrial complex at the present stage |
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| Тематика: | экономика | |
| Вид ресурса: | электронное немультимедийное издание | |
| Тип ресурса: | Статья | |
| Целевое назначение: | Научное | |
| Целевая аудитория: | Исследователь | |
| Аннотация: | This article is devoted to the consideration of how information technologies are used in practice in the agro-industrial complex at the present time. The main purpose of the study is to substantiate the effectiveness of these methods and to identify the main areas of use. The paper discusses the use of machine learning models to work with data in agriculture. The relevance of the study is justified by the fact that industry, as well as agriculture, are one of the most priority areas in our country. There is a need for the use of adaptive devices and new methods that will make it possible to achieve significant success in this area. The article is devoted to the consideration of the code implemented in Python, which can predict crop yields with high accuracy. By applying adaptive learning models and comparing different statistical models with each other, it is possible to identify the most accurate predictive indicators. | |
| Дата издания: | 2024 | |
| Дата загрузки: | 23.10.2024 | |
| Издательство: | SPIE | |