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Forecasting the Performance on Online Based System Using Evolutionary Programming Approach


Affiliations
1 Karpagam University, India
2 Karpagam Institute of Technology, India
     

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The online educational technologies offer many researchers and the student that provides exclusive opportunities of learning new possessions and gives the guidance of approaches to lead for success. The online based system collects the information and data on patterns. These data are included into the databases based on data mining applications. This paper focuses on students and online learners by predicting their performance based on the grade and the data which is included in the database. We implement a series of patterns classification and identify their performance based on the data which is logged in. Here, we have used the Genetic Algorithm for identifying the weighting of the learning process. The Genetic algorithm is used to improve the accuracy of the performance prediction.

Keywords

Evolutionary, Genetic Programming, Performance Prediction.
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  • Forecasting the Performance on Online Based System Using Evolutionary Programming Approach

Abstract Views: 274  |  PDF Views: 3

Authors

S. Saravanan
Karpagam University, India
R. Karthick
Karpagam Institute of Technology, India

Abstract


The online educational technologies offer many researchers and the student that provides exclusive opportunities of learning new possessions and gives the guidance of approaches to lead for success. The online based system collects the information and data on patterns. These data are included into the databases based on data mining applications. This paper focuses on students and online learners by predicting their performance based on the grade and the data which is included in the database. We implement a series of patterns classification and identify their performance based on the data which is logged in. Here, we have used the Genetic Algorithm for identifying the weighting of the learning process. The Genetic algorithm is used to improve the accuracy of the performance prediction.

Keywords


Evolutionary, Genetic Programming, Performance Prediction.



DOI: https://doi.org/10.36039/ciitaas%2F4%2F5%2F2012%2F106901.191-193