Improving hotel room demand forecasting with a hybrid GA-SVR methodology based on skewed data transformation, feature selection and parsimony tuning

[1]  Giovanni Seni,et al.  Ensemble Methods in Data Mining: Improving Accuracy Through Combining Predictions , 2010, Ensemble Methods in Data Mining.

[2]  Mikko Helle,et al.  Assessment of the State of the Blast Furnace High Temperature Region by Tuyere Core Drilling , 2009 .

[3]  Sheryl E. Kimes,et al.  A comparison of forecasting methods for hotel revenue management , 2003 .

[4]  D. A. Linkens,et al.  Roll load prediction—data collection, analysis and neural network modelling , 2004 .

[5]  Andreas Dengel,et al.  Meta-learning for evolutionary parameter optimization of classifiers , 2012, Machine Learning.

[6]  Andrés Sanz-García,et al.  Hotel Reservation Forecasting Using Flexible Soft Computing Techniques: A Case of Study in a Spanish Hotel , 2016, Int. J. Inf. Technol. Decis. Mak..

[7]  Andrés Sanz-García,et al.  GA-PARSIMONY: A GA-SVR approach with feature selection and parameter optimization to obtain parsimonious solutions for predicting temperature settings in a continuous annealing furnace , 2015, Appl. Soft Comput..

[8]  Zbigniew Michalewicz,et al.  Handling Constraints in Genetic Algorithms , 1991, ICGA.

[9]  George Panoutsos,et al.  Development of a parsimonious GA-NN ensemble model with a case study for Charpy impact energy prediction , 2011, Adv. Eng. Softw..

[10]  Jeffrey S. Zickus Forecasting for airline network revenue management : revenue and competitive impacts , 1998 .

[11]  Richard J. Duro,et al.  Evolutionary algorithm characterization in real parameter optimization problems , 2013, Appl. Soft Comput..

[12]  Hisham El-Shishiny,et al.  Dynamic room pricing model for hotel revenue management systems , 2011 .

[13]  D. Cox,et al.  An Analysis of Transformations , 1964 .

[14]  Ger Koole,et al.  Booking horizon forecasting with dynamic updating: A case study of hotel reservation data , 2011 .

[15]  Kurt Hornik,et al.  Misc Functions of the Department of Statistics (e1071), TU Wien , 2014 .

[16]  Yaochu Jin,et al.  Feature selection for high-dimensional classification using a competitive swarm optimizer , 2016, Soft Computing.

[17]  Russell C. H. Cheng,et al.  Optimal pricing policies for perishable products , 2005, Eur. J. Oper. Res..

[18]  Kin Keung Lai,et al.  A stochastic approach to hotel revenue optimization , 2005, Comput. Oper. Res..

[19]  V. Sadasivam,et al.  An integrated PSO for parameter determination and feature selection of ELM and its application in classification of power system disturbances , 2015, Appl. Soft Comput..

[20]  B. Sparks,et al.  The impact of online reviews on hotel booking intentions and perception of trust. , 2011 .

[21]  Asif Ekbal,et al.  MODE: multiobjective differential evolution for feature selection and classifier ensemble , 2015, Soft Computing.

[22]  Julio Fern'andez-Ceniceros,et al.  Methodology based on genetic optimisation to develop overall parsimony models for predicting temperature settings on annealing furnace , 2014 .

[23]  Jianming Ye On Measuring and Correcting the Effects of Data Mining and Model Selection , 1998 .