Analysis and design of a Taguchi–Grey based electricity demand predictor for energy management systems

Yao, Albert W.L.; Chi, Shou-Wei

doi:10.1016/j.enconman.2003.08.008

Cited by 76 publications

(35 citation statements)

References 3 publications

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“…On the other hand, it has been found in many papers using GST that this error can be much smaller if we use only a small portion of fresh observations, disregarding the old ones. This technique is known as the rolling modelling (Yao, 2004), or one can say that we define and use a forecasting window which remembers only some portion of fresh data.…”

Section: Condition Assessment and Forecasting In A Multidimensional Casementioning

confidence: 99%

Decomposition Of The Symptom Observation Matrix And Grey Forecasting In Vibration Condition Monitoring Of Machines

Cempel¹

2008

International Journal of Applied Mathematics and Computer Science

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With the tools of modern metrology we can measure almost all variables in the phenomenon field of a working machine, and many of the measured quantities can be symptoms of machine conditions. On this basis, we can form a symptom observation matrix (SOM) intended for condition monitoring and wear trend (fault) identification. On the other hand, we know that contemporary complex machines may have many modes of failure, called faults. The paper presents a method of the extraction of the information about faults from the symptom observation matrix by means of singular value decomposition (SVD), in the form of generalized fault symptoms. As the readings of the symptoms can be unstable, the moving average of the SOM is applied with success. An attempt to assess the diagnostic contribution of a primary symptom is made, and also an approach to assess the symptom limit value and to connect the SVD methodology with neural nets is considered. Finally, a condition forecasting problem is discussed and an application of grey system theory (GST) to symptom prognosis is presented. These possibilities are illustrated by processing data taken directly from the machine vibration condition monitoring area.

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Section: Condition Assessment and Forecasting In A Multidimensional Casementioning

confidence: 99%

Decomposition Of The Symptom Observation Matrix And Grey Forecasting In Vibration Condition Monitoring Of Machines

Cempel¹

2008

International Journal of Applied Mathematics and Computer Science

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“…Thus, the researchers develop the hybrid grey model for improving the forecasting ability, for example, Grey-Markov model [9], Grey-Fuzzy model [10], Grey-Taguchi model [11] and so on. Besides, some researchers try to change the stucture of grey forecasting models, including Grey Verhulst model [12], the nonlinear grey Bernoulli model (NGBM) [13][14], and Nash NGBM [15].…”

Section: Introductionmentioning

confidence: 99%

Forecasting Taiwan’s GDP by the Novel Weighted Average Nonlinear Grey Bernoulli Model

Hsin¹

2015

IJMO

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Abstract-In grey forecasting model, the average relative percentage error is an important criterion for assessing the forecasting precision. However, it seldom considers in-sample and out-of-sample tests at the same time. Besides, overestimation or underestimation usually exists when the original data has a rising or falling trend. Thus, this study proposes weighted average nonlinear grey Bernoulli model to solve above two problems. A weighted average moderates the effect of overestimation or underestimation. A new criterion which considers in-sample and out-of-sample tests at the same time indicates that the weighted average nonlinear grey Bernoulli model has the smallest modeling error. Finally, the proposed method is used to forecast Taiwan's GDP. The results show that Taiwan's GDP is steadily growing. It may serve as valuable information for policy makers and investors.

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“…The researchers try to improve the original models to get higher forecasting performance. They develop different types of grey forecasting models, including Grey-Markov model [11], Grey-Fuzzy model, Grey-Taguchi model [12], Grey Verhulst model [13], the nonlinear grey Bernoulli model(NGBM) [14,15], Nash NGBM [16] and so on. Besides, some researchers use different algorithm methods to solve the optimization problem.…”

Section: Introductionmentioning

confidence: 99%

Application of the Nash Nonlinear Grey Bernoulli Model for Forecasting Foreign Exchange Rate of Taiwan’s Top Two Trading Partners

Chen¹,

Hsin²

2016

J Stock Forex Trad

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The precise prediction of foreign exchange rate is very important for international traders and investors. This study adopts nonlinear grey Bernoulli model (NGBM) and Nash NGBM (NNGBM) to predict the currency exchange rate of Taiwan's two top trading partners, America and China. The simulation results show that Taiwan's currency will appreciate against USD and CNY from the fourth quarter of 2015 to the second quarter of 2016. The conclusions can act as reference for international traders and investors.

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Analysis and design of a Taguchi–Grey based electricity demand predictor for energy management systems

Cited by 76 publications

References 3 publications

Decomposition Of The Symptom Observation Matrix And Grey Forecasting In Vibration Condition Monitoring Of Machines

Decomposition Of The Symptom Observation Matrix And Grey Forecasting In Vibration Condition Monitoring Of Machines

Forecasting Taiwan’s GDP by the Novel Weighted Average Nonlinear Grey Bernoulli Model

Application of the Nash Nonlinear Grey Bernoulli Model for Forecasting Foreign Exchange Rate of Taiwan’s Top Two Trading Partners

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