Parameters optimization of GM(1,1) model based on artificial fish swarm algorithm
- 17 August 2012
- journal article
- Published by Emerald in Grey Systems: Theory and Application
- Vol. 2 (2), 166-177
- https://doi.org/10.1108/20439371211260144
Abstract
Purpose: The purpose of this paper is to enhance the forecast precision of GM(1,1) model using an improved artificial fish swarm algorithm.Design/methodology/approach: An optimization model of GM(1,1) model about identifying the parameters is proposed, which takes the minimum of the average relative error as objective function and takes the development coefficient and grey action quantity as decision variables, then an improved artificial fish swarm algorithm is designed to solve the optimization model.Findings: The results show that the proposed method may enhance the precision of GM(1,1) model, and have better performance than particle swarm optimization.Practical implications: The method exposed in the paper can be used to optimize the parameters of GM(1,1) model, which is used frequently to solve the economic and management problem.Originality/value: The paper succeeds in enhancing the forecast precision of GM(1,1) model using an improved artificial fish swarm algorithm.Keywords
This publication has 13 references indexed in Scilit:
- Modification of the fish swarm algorithm with particle swarm optimization formulation and communication behaviorApplied Soft Computing, 2011
- New buffer operators with variable weight based on average tempo and their optimizationGrey Systems: Theory and Application, 2011
- The construction of new weakening buffer operators and their applicationGrey Systems: Theory and Application, 2011
- Grey Unbiased GRM(1,1) Model Based on Accumulated Generating Operation in Reciprocal Number and its ApplicationAdvanced Materials Research, 2011
- An augmented Lagrangian fish swarm based method for global optimizationJournal of Computational and Applied Mathematics, 2011
- Forecasting stock indices using radial basis function neural networks optimized by artificial fish swarm algorithmKnowledge-Based Systems, 2011
- Grey number prediction using the grey modification model with progression techniqueApplied Mathematical Modelling, 2011
- Grey system theory-based models in time series predictionExpert Systems with Applications, 2010
- Optimization of Background Value in GM(1,1) ModelSystems Engineering - Theory & Practice, 2008
- The GM models that x(n) be taken as initial valueKybernetes, 2004