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ArticleUsing a set of GM(1,1) models to predict values of diagnostic symptoms

Maciej Tabaszewski2014

Article2014

Using a set of GM(1,1) models to predict values of diagnostic symptoms

Maciej Tabaszewski · Czeslaw Cempel

58 citations·0/0 files stored·Mechanical Systems and Signal Processing

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Grey System Theory Applications Reliability and Maintenance Optimization Machine Fault Diagnosis Techniques

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References

1982Control problems of grey systems 1989Introduction to Grey system theory 2009Grey system theory-based models in time series prediction 2010Forecasting energy consumption using a grey model improved by incorporating genetic programming 2003Forecast of the output value of Taiwan's opto-electronics industry using the Grey forecasting model 2003Analysis and design of a Taguchi–Grey based electricity demand predictor for energy management systems 2006A GM(1,1)–Markov chain combined model with an application to predict the number of Chinese international airlines 2003Application of grey modeling method to fitting and forecasting wear trend of marine diesel engines

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2019Data-based structure selection for unified discrete grey prediction model 2019Understanding cumulative sum operator in grey prediction model with integral matching 2020Forecasting tourism demand using fractional grey prediction models with Fourier series 2022A flexible grey Fourier model based on integral matching for forecasting seasonal PM2.5 time series 2017Explanations about grey information and framework of grey system modeling

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Details

Year2014

Typearticle

Published2014-08-28

VenueMechanical Systems and Signal Processing

ISSN-L0888-3270

Languageen

Citations58

Files0 public / 0

ShelfGrey System Theory Applications

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doi10.1016/j.ymssp.2014.08.013

openalex_workW1993327653

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2019A novel multi-information fusion grey model and its application in wear trend prediction of wind turbines

2020On unified framework for discrete-time grey models: Extensions and applications

2019A novel grey forecasting model and its application in forecasting the energy consumption in Shanghai