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In this paper, we propose a dynamic grey platform to modify the traditional algorithms by applying two new prediction algorithms for forecasting management. The proposed platform integrates a grey model (GM) with an exponentially weighted moving average EWMA controller known as the EGM model. The EGM model attempts to improve the forecast accuracy and efficiency. The prediction error of the EGM model...
This research designs a novel n-order grey model (GM) to predict import and export effects on air pollution trends in Taiwan. We also present an optimal refiner of Grey-Genetic Algorithms (GGA) to improve GM efficiency. In our test-beds, we propose several GM models for the prediction of air pollution trends. The simple model (GM(1, 1)) and the n-order multiple model (GM(1, N) and RGM(1, N)) are utilized...
This study proposes an optimal controller of Grey-Genetic Algorithms (GGA) to improve the prediction efficiency of grey theory models (GM). In this research, we design the different experimental schemes for the improving efficiency of the prediction models. The simple model (GM(1, 1)) and multiple model (GM(1,N)) are applied in the short-lifecycle product prediction system that was presented and evaluated...
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