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A Machine Learning Approach to Determine Abundance of Inclusions in Stainless Steel.

, , , , , , and . HAIS, volume 11734 of Lecture Notes in Computer Science, page 504-513. Springer, (2019)

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Artificial Neural Networks, Sequence-to-Sequence LSTMs, and Exogenous Variables as Analytical Tools for NO2 (Air Pollution) Forecasting: A Case Study in the Bay of Algeciras (Spain)., , , , , and . Sensors, 21 (5): 1770 (2021)Ro-Ro Freight Forecasting Based on an ANN-SVR Hybrid Approach. Case of the Strait of Gibraltar., , , , and . IWANN (1), volume 11506 of Lecture Notes in Computer Science, page 818-831. Springer, (2019)A Comparison of Forecasting Methods for Ro-Ro Traffic: A Case Study in the Strait of Gibraltar., , , , and . DepCoS-RELCOMEX, volume 286 of Advances in Intelligent Systems and Computing, page 345-353. Springer, (2014)A machine learning-based forecasting system of perishable cargo flow in maritime transport., , , , and . Neurocomputing, (2021)A Genetic Algorithm and Neural Network Stacking Ensemble Approach to Improve NO2 Level Estimations., , , , , and . IWANN (1), volume 11506 of Lecture Notes in Computer Science, page 856-867. Springer, (2019)Container Demand Forecasting at Border Posts of Ports: A Hybrid SARIMA-SOM-SVR Approach., , , , and . OLA, volume 1173 of Communications in Computer and Information Science, page 69-81. Springer, (2020)Forecasting Freight Inspection Volume Using Bayesian Regularization Artificial Neural Networks: An Aggregation-Disaggregation Procedure., , , and . SOCO-CISIS-ICEUTE, volume 649 of Advances in Intelligent Systems and Computing, page 179-187. Springer, (2017)Efficient goods inspection demand at ports: a comparative forecasting approach., , , , and . ITOR, 26 (5): 1906-1934 (2019)A two-stage forecasting approach for short-term intermodal freight prediction., , , , and . Int. Trans. Oper. Res., 26 (2): 642-666 (2019)Hourly pollutants forecasting using a deep learning approach to obtain the AQI., , , , and . Log. J. IGPL, 31 (4): 722-738 (July 2023)