Prediction of gross domestic product development by Takagi-Sugeno fuzzy inference systems

The paper presents the possibility of the design and application of Takagi-Sugeno fuzzy inference system in predicting of gross domestic product development by designing a prediction models whose accuracy is superior to the models used in praxis.

[1]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[2]  D. Rubinfeld,et al.  Econometric models and economic forecasts , 2002 .

[3]  Ebrahim H. Mamdani,et al.  An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller , 1999, Int. J. Hum. Comput. Stud..

[4]  Risto Miikkulainen,et al.  Fast Reinforcement Learning through Eugenic Neuro-Evolution , 1999 .

[5]  Bharat Trehan,et al.  Using monthly data to predict quarterly output , 1996 .

[6]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[7]  E. H. Mandami Application of Fuzzy Logic to Approximate Reasoning using Linguistic Synthesis , 1977 .

[8]  Ludmila I. Kuncheva,et al.  Fuzzy Classifier Design , 2000, Studies in Fuzziness and Soft Computing.

[9]  S. Hyakin,et al.  Neural Networks: A Comprehensive Foundation , 1994 .

[10]  Jianwei Zhang,et al.  A New Type of Fuzzy Logic System for Adaptive Modeling and Control , 1997, Fuzzy Days.

[11]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[12]  Greg Tkacz,et al.  Forecasting GDP Growth Using Artificial Neural Networks , 1999 .

[13]  Oscar Castillo,et al.  Soft Computing for Control of Non-Linear Dynamical Systems , 2001 .

[14]  John W Prior Eugenic Evolution for Combinatorial Optimization , 1998 .

[15]  M. Sugeno FUZZY MEASURES AND FUZZY INTEGRALS—A SURVEY , 1993 .