Decision Science Letters (Jul 2015)

Optimization of continuous ranked probability score using PSO

  • Seyedeh Atefeh Mohammadi,
  • Morteza Rahmani,
  • Majid Azadi

DOI
https://doi.org/10.5267/j.dsl.2015.4.001
Journal volume & issue
Vol. 4, no. 3
pp. 373 – 378

Abstract

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Weather forecast has been a major concern in various industries such as agriculture, aviation, maritime, tourism, transportation, etc. A good weather prediction may reduce natural disasters and unexpected events. This paper presents an empirical investigation to predict weather temperature using continuous ranked probability score (CRPS). The mean and standard deviation of normal density function are linear combination of the components of ensemble system. The resulted optimization model has been solved using particle swarm optimization (PSO) and the results are compared with Broyden–Fletcher–Goldfarb–Shanno (BFGS) method. The preliminary results indicate that the proposed PSO provides better results in terms of root-mean-square deviation criteria than the alternative BFGS method.

Keywords