Ro-Ro Freight Prediction Using a Hybrid Approach Based on Empirical Mode Decomposition, Permutation Entropy and Artificial Neural Networks

José Antonio Moscoso López, Juan Jesús Ruiz-Aguilar, Javier González-Enrique, Daniel Urda, Héctor Mesa, Ignacio J. Turias. Ro-Ro Freight Prediction Using a Hybrid Approach Based on Empirical Mode Decomposition, Permutation Entropy and Artificial Neural Networks. In Hilde Pérez García, Lidia Sánchez-González, Manuel Castejón Limas, Héctor Quintián-Pardo, Emilio S. Corchado Rodríguez, editors, Hybrid Artificial Intelligent Systems - 14th International Conference, HAIS 2019, León, Spain, September 4-6, 2019, Proceedings. Volume 11734 of Lecture Notes in Computer Science, pages 563-574, Springer, 2019. [doi]

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