Seasonal SVR with FOA algorithm for single-step and multi-step ahead forecasting in monthly inbound tourist flow

This publication has 26 references indexed in Scilit:

• A new fuzzy time series forecasting model combined with ant colony optimization and auto-regression
  Knowledge-Based Systems, 2015
• SVR with hybrid chaotic genetic algorithms for tourism demand forecasting
  Applied Soft Computing, 2011
• Multi-objective rule mining using a chaotic particle swarm optimization algorithm
  Knowledge-Based Systems, 2009
• Support vector regression with genetic algorithms in forecasting tourism demand
  Tourism Management, 2007
• A tutorial on support vector regression
  Statistics and Computing, 2004
• Practical selection of SVM parameters and noise estimation for SVM regression
  Neural Networks, 2004
• A fast and elitist multiobjective genetic algorithm: NSGA-II
  IEEE Transactions on Evolutionary Computation, 2002
• Time series forecasts of international travel demand for Australia
  Tourism Management, 2002
• A practitioners guide to time-series methods for tourism demand forecasting — a case study of Durban, South Africa
  Tourism Management, 2001
• A neural network model to forecast Japanese demand for travel to Hong Kong
  Tourism Management, 1999