Determination of the athletes' anaerobic threshold using machine learning methods

2022 ◽  
Vol 73 ◽  
pp. 103414
Author(s):  
Alexander Chikov ◽  
Nikolay Egorov ◽  
Dmitry Medvedev ◽  
Svetlana Chikova ◽  
Evgeniy Pavlov ◽  
...  
Keyword(s):  
Machine Learning ◽  
Anaerobic Threshold ◽  
Learning Methods ◽  
Machine Learning Methods

scholarly journals Application of machine learning methods in big data analytics at management of contracts in the construction industry

2018 ◽  
Vol 170 ◽  
pp. 01106 ◽  
Author(s):  
Marina Valpeters ◽  
Ivan Kireev ◽  
Nikolay Ivanov
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Construction Industry ◽  
Big Data Analytics ◽  
Machine Learning Algorithms ◽  
Prognostic Models ◽  
Problem Analysis ◽  
Learning Methods ◽  
Machine Learning Methods

The number of experts who realize the importance of big data continues to increase in various fields of the economy. Experts begin to use big data more frequently for the solution of their specific objectives. One of the probable big data tasks in the construction industry is the determination of the probability of contract execution at a stage of its establishment. The contract holder cannot guarantee execution of the contract. Therefore it leads to a lot of risks for the customer. This article is devoted to the applicability of machine learning methods to the task of determination of the probability of a successful contract execution. Authors try to reveal the factors influencing the possibility of contract default and then try to define the following corrective actions for a customer. In the problem analysis, authors used the linear and non-linear algorithms, feature extraction, feature transformation and feature selection. The results of investigation include the prognostic models with a predictive force based on the machine learning algorithms such as logistic regression, decision tree, randomize forest. Authors have validated models on available historical data. The developed models have the potential for practical use in the construction organizations while making new contracts.

Application of machine learning methods for automatic interpretation of open hole logging data

2020 ◽  
pp. 44-47
Author(s):  
M.A. Basyrov ◽  
◽  
A.V. Akinshin ◽  
I.R. Makhmutov ◽  
Yu.D. Kantemirov ◽  
...  
Keyword(s):  
Machine Learning ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Automatic Interpretation ◽  
Open Hole
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