Forecasting SMEs' credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach
In recent years, financial institutions (FIs) have tentatively utilized supply chain finance (SCF)
as a means of solving the financing issues of small and medium-sized enterprises (SMEs) …
as a means of solving the financing issues of small and medium-sized enterprises (SMEs) …
Forecasting short-term electricity consumption using the adaptive grey-based approach—An Asian case
The overall electricity consumption, treated as a primary guideline for electricity system
planning, is a major measurement to indicate the degree of a nation's development. The …
planning, is a major measurement to indicate the degree of a nation's development. The …
A novel gray forecasting model based on the box plot for small manufacturing data sets
Efficiently controlling the early stages of a manufacturing system is an important issue for
enterprises. However, the number of samples collected at this point is usually limited due to …
enterprises. However, the number of samples collected at this point is usually limited due to …
A genetic algorithm-based virtual sample generation technique to improve small data set learning
DC Li, IH Wen - Neurocomputing, 2014 - Elsevier
While back-propagation neural networks (BPNN) are effective learning tools for building non-
linear models, they are often unstable when using small-data-sets. Therefore, in order to …
linear models, they are often unstable when using small-data-sets. Therefore, in order to …
An improved grey-based approach for early manufacturing data forecasting
Global competition has shortened product life cycles and makes the trend of industrial
demand not easily forecasted. Therefore, one of the key points that will enable enterprises to …
demand not easily forecasted. Therefore, one of the key points that will enable enterprises to …
Reducing myopic behavior in FMS control: A semi-heterarchical simulation–optimization approach
GZ Rey, T Bonte, V Prabhu, D Trentesaux - Simulation Modelling Practice …, 2014 - Elsevier
Heterarchical FMS control architectures localize decisional capabilities in each entity,
resulting in highly reactive, low complexity control architectures. Unfortunately, these …
resulting in highly reactive, low complexity control architectures. Unfortunately, these …
Machine learning enables electrical resistivity modeling of printed lines in aerosol jet 3D printing
Among various non-contact direct ink writing techniques, aerosol jet printing (AJP) stands
out due to its distinct advantages, including a more adaptable working distance (2–5 mm) …
out due to its distinct advantages, including a more adaptable working distance (2–5 mm) …
Extreme data mining: Inference from small datasets
R Andonie - International Journal of Computers …, 2010 - digitalcommons.cwu.edu
Neural networks have been applied successfully in many fields. However, satisfactory
results can only be found under large sample conditions. When it comes to small training …
results can only be found under large sample conditions. When it comes to small training …
Extending attribute information for small data set classification
DC Li, CW Liu - IEEE Transactions on Knowledge and Data …, 2010 - ieeexplore.ieee.org
Data quantity is the main issue in the small data set problem, because usually insufficient
data will not lead to a robust classification performance. How to extract more effective …
data will not lead to a robust classification performance. How to extract more effective …
A forecasting model for small non-equigap data sets considering data weights and occurrence possibilities
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 …
make accurate forecasts. Grey system theory is one of the approaches to deal with this …