Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
A non-parametric learning algorithm for small manufacturing data sets
Expert Systems with Applications: An International Journal
A grey-based rough approximation model for interval data processing
Information Sciences: an International Journal
The use of grey relational analysis in solving multiple attribute decision-making problems
Computers and Industrial Engineering
Forecasting analysis by using fuzzy grey regression model for solving limited time series data
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Forecasting integrated circuit output using multivariate grey model and grey relational analysis
Expert Systems with Applications: An International Journal
Grey system theory-based models in time series prediction
Expert Systems with Applications: An International Journal
An improved grey-based approach for early manufacturing data forecasting
Computers and Industrial Engineering
Computers and Industrial Engineering
Computers and Industrial Engineering
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In the early stages of manufacturing systems, it is often difficult to obtain sufficient data to make accurate forecasts. Grey system theory is one of the approaches to deal with this issue, as it uses fairly small sets to construct forecasting models. Among published grey models, the current non-equigap grey models can deal with data having unequal gaps, and have been applied in various fields. However, these models usually use fixed modeling procedures that do not consider data growth trend differences. This paper utilizes the trend and potency tracking method to determine the parameter @a of the background value to build an adaptive non-equigap grey model to improve forecasting performance. The experimental results indicate that the proposed method considers that data occurrence properties can obtain better forecasting results.