  Here, we have employed Principal Component Analysis (PCA) and Linear
Discriminant Analysis (LDA) to analyze Mie calculated UV-Vis spectra of gold
nanospheres (GNS). Eigen spectra of PCA perform the Fano type resonances.3D
vector field spectra reveal the Homoclinic orbit Lorenz attractor. Quantum
confinement effects are observed by 3D representation of LDA. Standing wave
patterns resulting from oscillations of ion acoustic phonon and electron waves
are illustrated through the eigen spectra of LDA. Such capabilities of GNPs
have brought high attention for the high energy density physics applications.
Furthermore, accurate prediction of gold nanoparticle (GNP) sizes using machine
learning could provide rapid analysis without the need for expensive analysis.
Two hybrid algorithms consist of unsupervised PCA and two different supervised
ANN have been used to estimate the diameters of GNPs. PCA based artificial
neural network (ANN) were found to estimate the diameters with a high accuracy.
