Journal ArticleDOI
Grey system theory-based models in time series prediction
TLDR
The simulation results show that modified grey models have higher performances not only on model fitting but also on forecasting, and the modified GM(1,1) using Fourier series in time is the best in model fitting and forecasting.Abstract:
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, fuzzy predictors, evolutionary and genetic algorithms. In this paper, the accuracies of different grey models such as GM(1,1), Grey Verhulst model, modified grey models using Fourier Series is investigated. Highly noisy data, the United States dollar to Euro parity between the dates 01.01.2005 and 30.12.2007, are used to compare the performances of the different models. The simulation results show that modified grey models have higher performances not only on model fitting but also on forecasting. Among these grey models, the modified GM(1,1) using Fourier series in time is the best in model fitting and forecasting.read more
Citations
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Grey system model with the fractional order accumulation
TL;DR: The perturbation theory of least squares method is applied and the new Grey system model with the fractional order accumulation provides very remarkable predication performance compared with the traditional Grey model for small sample.
Journal ArticleDOI
Evaluating green supplier development programs with a grey-analytical network process-based methodology
TL;DR: A grey analytical network process-based (grey ANP-based) model is introduced to identify green supplier development programs that will effectively improve suppliers’ performance and is comprehensively evaluated with explicit consideration of suppliers�’ involvement propensity levels.
Journal ArticleDOI
Time series analysis and long short-term memory neural network to predict landslide displacement
TL;DR: Wang et al. as discussed by the authors proposed a dynamic model to predict landslide displacement, based on time series analysis and long short-term memory (LSTM) neural network, which can be used to effectively predict the displacement of step-wise landslides in the Three Gorges Reservoir Area (TGRA), the Baishuihe landslide and Bazimen landslide.
Journal ArticleDOI
An Online Optimal Dispatch Schedule for CCHP Microgrids Based on Model Predictive Control
TL;DR: An online optimal operation approach for CCHP microgrids based on model predictive control with feedback correction to compensate for prediction error is proposed and demonstrates the effectiveness of the proposed approach with better matching between demand and supply.
Journal ArticleDOI
Models for forecasting growth trends in renewable energy
Sang-Bing Tsai,Sang-Bing Tsai,You-Zhi Xue,Jianyu Zhang,Quan Chen,Yubin Liu,Jie Zhou,Weiwei Dong +7 more
TL;DR: In this paper, the authors used three grey prediction models, the GM(1,1) model, the NGBM( 1,1), and the grey Verhulst model, for theoretical derivation and scientific verification.
References
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