A combined forecasting approach based on fuzzy soft sets

  • Authors:

  • Zhi Xiao;Ke Gong;Yan Zou

  • Affiliations:

  • School of Economics and Business Administration, Chongqing University, Chongqing 400044, PR China;School of Economics and Business Administration, Chongqing University, Chongqing 400044, PR China;College of Mathematics and Computer Science, Chongqing Normal University, Chongqing 400047, PR China

  • Venue:
  • Journal of Computational and Applied Mathematics
  • Year:
  • 2009

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Abstract

Forecasting the export and import volume in international trade is the prerequisite of a government's policy-making and guidance for a healthier international trade development. However, an individual forecast may not always perform satisfactorily, while combination of forecasts may result in a better forecast than component forecasts. We believe the component forecasts employed in combined forecasts are a description of the actual time series, which is fuzzy. This paper attempts to use forecasting accuracy as the criterion of fuzzy membership function, and proposes a combined forecasting approach based on fuzzy soft sets. This paper also examines the method with data of international trade from 1993 to 2006 in the Chongqing Municipality of China and compares it with a combined forecasting approach based on rough sets and each individual forecast. The experimental results show that the combined approach provided in this paper improves the forecasting performance of each individual forecast and is free from a rough sets approach's restrictions as well. It is a promising forecasting approach and a new application of soft sets theory.