Artificial Neural Network Model to Predict Academic Results in Mathematics II

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書誌詳細
著者:	Incio-Flores, Fernando Alain, Capuñay-Sanchez, Dulce Lucero, Estela-Urbina, Ronald Omar
フォーマット:	artículo
状態:	Versión publicada
出版日付:	2023
その他の書誌記述:	Objective. This article shows the design and training of an artificial neural network (ANN) to predict academic results of Civil Engineering students of the Fabiola Salazar Leguía National Intercultural University, from Bagua-Peru, in the subject of Mathematics II. Method. The CRISP-DM methodology was used, surveys were conducted to collect the data, and the RNA model was implemented in the Matlab software using the nnstart command and two learning algorithms: Scaled Conjugate Gradient (SCG) and Levenberg-Marquardt (LM). The performance of the model was evaluated through the mean square error and the correlation coefficient. Conclusions. The LM algorithm achieved better prediction effectiveness.
国:	Portal de Revistas UNA
機関:	Universidad Nacional de Costa Rica
Repositorio:	Portal de Revistas UNA
言語:	Español Inglés Portugués
OAI Identifier:	oai:www.revistas.una.ac.cr:article/14516
オンライン･アクセス:	https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/14516
キーワード:	Red neuronal artificial rendimiento académico predicción