In this study, an analysis of the perturbation factors and fractional order derivatives is performed for the novel
singular model. The design of the perturbed fractional order singular model is presented by using the traditional
form of the Lane-Emden along with the detail of singular points, fractional order, shape, and perturbed factors.
The analysis of the perturbation factors and fractional order terms for the singular model is provided in two steps
by taking three different values of the perturbed term as well as fractional order derivatives. The numerical
analysis of the perturbation and fractional order terms for the novel fractional Meyer wavelet neural network
(FMWNN) along with the global and local search effectiveness of the genetic algorithm (GA) and active-set algorithm
(ASA)
called
as
FMWNN-GAASA.
The
modeling
of
the
FMWNN
is
presented
in
terms
of
mean
square

error,
while
the
optimization
is
performed
through
the
GAASA.
The
authentication,
validation,
excellence,
and

correctness
of
the
singular
model
are
observed
by
using
the
comparative
performances
of
the
obtained
and
the

reference
solutions.
The
stability
of
the
proposed
stochastic
scheme
is
observed
through
the
statistical
performances
for
taking
large
datasets
to
present
the
analysis
of
the
perturbation
and
fractional
order
terms.