Reset filters

Search publications


By keyword
By department

No publications found.

 

Analysis of input set characteristics and variances on k-fold cross validation for a Recurrent Neural Network model on waste disposal rate estimation

Author(s): Vu HL; Ng KTW; Richter A; An C;

The use of machine learning techniques in waste management studies is increasingly popular. Recent literature suggests k-fold cross validation may reduce input dataset partition uncertainties and minimize overfitting issues. The objectives are to quantify t ...

Article GUID: 35287077


-   Page 1 / 1   -