Forecasting Natural Gas Consumption Using Pso Optimized Least Squares Support Vector Machines

@inproceedings{Iranmanesh2011ForecastingNG,
  title={Forecasting Natural Gas Consumption Using Pso Optimized Least Squares Support Vector Machines},
  author={Hossein Iranmanesh and Majid Abdollahzade and Arash Miranian},
  year={2011}
}
This paper proposes an effective model based on the least squares support vector machines (LSSVM) and the particle swarm optimization (PSO), termed PSO-LSSVM, for prediction of natural gas consumption, as an important energy resource. The salient feature of mapping nonlinear data into high dimension feature space, distinguishes LS-SVM as a powerful approach for forecasting and estimation. Optimization of the model’s parameters by a fast and efficient PSO algorithm results in an optimized model… CONTINUE READING