Peramalan Jumlah Penumpang Kereta Api di Indonesia dengan Resilient Back-Propagation (Rprop) Neural Network
Train scheduling affects the level of customer satisfaction and profitability of the train service provider. The prediction method of Back-propagation Neural Network (BPNN) has relatively slow convergence. Therefore, this study uses Resilient Back-propagation (Rprop) because it has a more fast conve...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Department of Mathematics, UIN Sunan Ampel Surabaya
2018
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/b652028a1e394deb90516ab38c84fc0c |
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