Palladium is an element of PGM group that has significant physical properties. This leads to more attention to this metal. Due to vast applications of palladium in industry and its usage in jewelry, its price plays an important role in economic. Therefore, forecasting its price is crucial subject in economic and engineering design. This paper proposes the model GM(1,1) to predict the Palladium ...

The research scope of grey relational analysis has not been developed in recent years, and the exiting GRA models are all based on three perspectives, including distance perspective, slope perspective, and area perspective. Under this situation, a novel model called grey relational analysis based on angle perspective (GRAAP) was developed in this paper for the first time, and this model can exp...

Being able to forecast time series accurately has been quite a popular subject for researchers both in the past and at present. However, the lack of ability of conventional analysis methods to forecast time series that are not smooth leads the scientists and researchers to resort to various forecasting models that have different mathematical backgrounds, such as artificial neural networks, fuzz...

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The grey theory mainly works on systems analysis with poor, incomplete or uncertain messages. The popular grey model, GM(1,1) is efficient for long-term port throughput forecasting. However, it is imperfect when the throughput increases in the curve with S type or the increment of throughput is in the saturation stage. In this case, the throughput forecasting error of grey system model will bec...

The advantages and disadvantages of BP neural network and grey Verhulst model for time series prediction are analyzed respectively, this article proposes a new time series forecasting model for the time series growth in S-type or growth being saturated. From the data fitting's viewpoint, the new model named grey Verhulst neural network is established based on grey Verhulst model and BP neural n...

An enhanced grey clustering analysis method based on accumulation sequences using grey relational analysis (AGRA) is put forward for specifying hierarchies of clusters in panel data. The clustering method can handle panel data containing N samples, each of which hasm time series of indicators for which the observations for a given time series can bemeasured at different times than other series ...