Real-valued genetic algorithms for fuzzy grey prediction system
Fuzzy Sets and Systems
Genetic Algorithms Plus Data Structures Equals Evolution Programs
Genetic Algorithms Plus Data Structures Equals Evolution Programs
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Expert Systems with Applications: An International Journal
Forecasting integrated circuit output using multivariate grey model and grey relational analysis
Expert Systems with Applications: An International Journal
An expert system for forecasting mutual funds in Greece
International Journal of Electronic Finance
Computers and Electronics in Agriculture
Computers and Industrial Engineering
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In this article, an improved nonlinear grey Bernoulli model by using genetic algorithms to solve the optimal parameter estimation problem of small amount of data used in the forecast is proposed. The time series data of Taiwan's integrated circuit industry (1990-2007) was used as the test data set. In addition, the mean absolute percentage error and the root mean square percentage error were used to compare the performance of the forecast models. The results showed that the improved nonlinear grey Bernoulli model is more accurate and performs better than the traditional GM(1,1) model and grey Verhulst model. Moreover, the optimum mechanisms indeed improve the grey model of prediction accuracy by using genetic algorithms approach.