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Disambiguation of "de Pisón Ascacibar, Francisco J. Martínez"

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Application of Genetic Algorithms to Optimize a Truncated Mean k-Nearest Neighbours Regressor for Hotel Reservation Forecasting.

, , , and . HAIS (1), volume 7208 of Lecture Notes in Computer Science, page 79-90. Springer, (2012)

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Francisco Javier Martínez Concha

Gerardo Francisco Ramírez-Martínez

Francisco Martinez Andueza

Francisco-José Martínez y Portillo

Francisco Javier Martinez Torres

 

Other publications of authors with the same name

Estimation of Daily Global Horizontal Irradiation Using Extreme Gradient Boosting Machines., , , and . SOCO-CISIS-ICEUTE, volume 527 of Advances in Intelligent Systems and Computing, page 105-113. (2016)Hybrid Modelling of Multilayer Perceptron Ensembles for Predicting the Response of Bolted Lap Joints., , , and . Logic Journal of the IGPL, 23 (3): 451-462 (2015)Artificial Intelligence Models for Assessing the Evaluation Process of Complex Student Projects., , , and . IEEE Trans. Learn. Technol., 16 (5): 694-707 (October 2023)Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method., , , and . Sensors, 19 (11): 2483 (2019)An Overall Performance Comparative of GA-PARSIMONY Methodology with Regression Algorithms., , , , and . SOCO-CISIS-ICEUTE, volume 299 of Advances in Intelligent Systems and Computing, page 53-62. Springer, (2014)Application of Genetic Algorithms to Optimize a Truncated Mean k-Nearest Neighbours Regressor for Hotel Reservation Forecasting., , , and . HAIS (1), volume 7208 of Lecture Notes in Computer Science, page 79-90. Springer, (2012)New Hybrid Methodology Based on Particle Swarm Optimization with Genetic Algorithms to Improve the Search of Parsimonious Models in High-Dimensional Databases., , and . HAIS, volume 13469 of Lecture Notes in Computer Science, page 335-347. Springer, (2022)Hybrid Intelligent Parsimony Search in Small High-Dimensional Datasets., , , and . HAIS, volume 14001 of Lecture Notes in Computer Science, page 384-396. Springer, (2023)Improving Hotel Room Demand Forecasting with a Hybrid GA-SVR Methodology Based on Skewed Data Transformation, Feature Selection and Parsimony Tuning., , , , and . HAIS, volume 9121 of Lecture Notes in Computer Science, page 632-643. Springer, (2015)Hotel Reservation Forecasting Using Flexible Soft Computing Techniques: A Case of Study in a Spanish Hotel., , , , and . Int. J. Inf. Technol. Decis. Mak., 15 (5): 1211-1234 (2016)