ABSTRACT
Abstract ................................................................................................... 77 4.1 Introduction .................................................................................... 78 4.2 Taguchi Method ............................................................................. 78 4.3 Methodology .................................................................................. 80 4.4 Results and Discussion .................................................................. 83 4.5 Conclusion ..................................................................................... 86 Keywords ................................................................................................ 87 References ............................................................................................... 87
ABSTRACT
The objective of this work is to apply genetic programming (GP) as a machine learning technique in the context of nanofiber diameter detection. Defined functions automatically enable GP to describe the useful and reusable subroutines dynamically during a run. By using this method, a mathematical equation can be obtained without any restriction. Several relationships based on GP to determine the nanofiber diameter were proposed. The result showed that all solutions had high regression coefficient which indicted the accuracy of solution predictions. Solution E had the best accuracy percentage and the lowest error percentage.
