Syaharuddin, Syaharuddin and Pramita, D and Nusantara, T and Subanji, Subanji and Negara, Habibi Ratu Perwira (2020) Analysis of accuracy parameters of ANN backpropagation algorithm through training and testing of hydro-climatology data based on GUI MATLAB. AIP Conference Proceedings, 413 (1). pp. 1-7.
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Analysis of accuracy parameters of ANN backpropagation.pdf - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) |
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Cek Plagiat_Analysis of accuracy parameters of ANN backpropagation algorithm through training and testing of hydro-climatology data based on GUI MATLAB.pdf - Supplemental Material Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) |
Abstract
The authors have developed a GUI Matlab to simplify the process of predicting Hydroclimatology data using ANN Back Propagation method. Five data for training, testing, and prediction were used. The data, i.e. rainfall, air humidity, duration of shine, temperature, and wind speed are taken from the last ten years with matrix input size m x n. Each data is trained 21 times using a combination of the activation functions (logsig, tansig, and purelin) and training methods (traingda, traingdx, and trainrp). The result of the training data was that the logsig function and trainrp on each layer are the best formulas in conducting training, testing, and predictions with an accuracy of 99.71%. This result is obtained from parameter settings including epochs of 1000, learning rate of 0.7, goal error of 0.0001, and training steps of 1.
Item Type: | Article |
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Subjects: | 01 MATHEMATICAL SCIENCES > 0103 Numerical and Computational mathematics > 010301 Numerical Analysis 01 MATHEMATICAL SCIENCES > 0103 Numerical and Computational mathematics > 010302 Numerical Solution of Differential and Integral Equations |
Divisions: | Fakultas Tarbiyah dan Keguruan > Jurusan Tadris Matematika |
Depositing User: | Habibi Habibi Perwira Ratu Perwira Negara |
Date Deposited: | 10 May 2023 07:35 |
Last Modified: | 10 May 2023 07:35 |
URI: | http://repository.uinmataram.ac.id/id/eprint/3035 |
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