Analysis of digital technologies in the agri-food sector based on big data analysis methods

2021 ◽  
pp. 334-344
Author(s):  
Yulia Sergeevna Otmakhova ◽  
Dmitry Alexeevich Devyatkin ◽  
Natalia Ivanovna Usenko
2017 ◽  
Vol 207 ◽  
pp. 354-362 ◽  
Author(s):  
Yang Zhao ◽  
Peng Liu ◽  
Zhenpo Wang ◽  
Lei Zhang ◽  
Jichao Hong

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Hao Cui ◽  
Zhiqiang Peng

Although the validity of the physical activity questionnaire is low, the questionnaire is still the most commonly used measurement tool for physical activity research in China in the past 10 years. In the era of big data, research in the field of physical activity in China needs to be more effective, economical, convenient, and suitable for long-term, large-sample research tools. Acceleration detection technology, heart rate detection technology, and GPS technology are the mainstream technologies for measuring the energy consumption of physical activity in wearable devices. The application of data mining and machine learning methods further enhances the validity of the test. Domestic smart wearable devices are not effective in estimating energy consumption but still have a large space for technical improvement. Smart wearable devices have a very broad application prospect in the field of big data research in physical activity. The impact of smart wearable device technology and big data analysis methods on physical activity research will be far-reaching and may lead to major changes in research concepts, research tools, and data analysis methods.


2021 ◽  
Vol 192 ◽  
pp. 2633-2640
Author(s):  
Veselska Olga ◽  
Ziubina Ruslana ◽  
Fіnenko Yuriy ◽  
Nikodem Joanna

Author(s):  
А.Н. Копайгородский ◽  
Т.Г. Мамедов

В статье рассмотрены методы построения интеллектуальной информационной системы для поддержки экспертных решений по стратегическому инновационному развитию энергетики. Обоснована необходимость применения методов анализа Больших данных (Big Data). Представлена архитектура интегрированного хранилища интеллектуальной информационной системы, основным компонентом которой является система онтологий, объединяющая данные и знания из различных источников. The article discusses methods of building an intelligent information system to support expert decisions on strategic innovative development of the energy sector. The necessity of using Big Data analysis methods has been substantiated. Architecture of an integrated repository of an intelligent information system is presented, in which the main component is a system of ontologies on the basis of which information, data and knowledge from various sources are combined.


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