scholarly journals Application of intellectual data analysis methods for digital educational platform

Author(s):  
Kristina Zhatkina ◽  
Oksana Kreider

This article describes the possibility of using data mining techniques. In order to join new carpet participants, it is necessary to understand that the system of interaction with them is public educational services. To implement digital educational platforms, it is proposed to create an agent that collects information about sites, and also selects and tests the architecture of the neural network to build an individual trajectory that is trained using the competency-based model.

2011 ◽  
Vol 29 (3) ◽  
pp. 467-491 ◽  
Author(s):  
H. Vanhamäki ◽  
O. Amm

Abstract. We present a review of selected data-analysis methods that are frequently applied in studies of ionospheric electrodynamics and magnetosphere-ionosphere coupling using ground-based and space-based data sets. Our focus is on methods that are data driven (not simulations or statistical models) and can be used in mesoscale studies, where the analysis area is typically some hundreds or thousands of km across. The selection of reviewed methods is such that most combinations of measured input data (electric field, conductances, magnetic field and currents) that occur in practical applications are covered. The techniques are used to solve the unmeasured parameters from Ohm's law and Maxwell's equations, possibly with help of some simplifying assumptions. In addition to reviewing existing data-analysis methods, we also briefly discuss possible extensions that may be used for upcoming data sets.


2015 ◽  
Vol 738-739 ◽  
pp. 191-196
Author(s):  
Yun Jie Li ◽  
Hui Song

In this paper, several data mining techniques were discussed and analyzed in order to achieve the objective of human daily activities recognition based on a continuous sensing data set. The data mining techniques of decision tree, Naïve Bayes and Neural Network were successfully applied to the data set. The paper also proposed an idea of combining the Neural Network with the Decision Tree, the result shows that it works much better than the typical Neural Network and the typical Decision Tree model.


Author(s):  
Alla G. Kravets ◽  
◽  
Natalia A. Salnikova ◽  

In the work, the problem of forecasting technological development trends was considered. A review of the sources of the global patent space, an analysis of technological development trends, a survey of data sources for training the neural network were carried out. Existing data mining techniques were analyzed for more accurate and faster forecasting. A module for predictive modeling of trends in technological development was developed, algorithms for the module for predictive modeling of trends in technological development were described.


Author(s):  
P. Jeanty ◽  
M. Delsaut ◽  
L. Trovalet ◽  
H. Ralambondrainy ◽  
J.D. Lan-Sun-Luk ◽  
...  

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