Journal of Kufa for Mathematics and Computer

In this paper, we study semiparametric
regression models with spline smoothing, and
determining the numbers of knots and their
locations by using some statistical criteria, a
simulation model has been performed.

In this paper we are interested in
studying of bifurcation solutions of bifurcation
equation (nonlinear system of algebraic
equations with four or six parameters). Also, we
found a new geometrical description of the
Discriminate set(bifurcation set) with bifurcation
spreading of the number of regular solutions in
every region. In addution, we calculate the
topological indices of the solutions of the
problem.

In this paper, we introduce and study contra T
*
- continuous functions these are functions
f: XY such that the inverse image of every open set in Y is T
*
-closed in X. Several properties of this type
of functions are proved.

This paper study the bifurcation solutions of
a System of nonlinear differential equations,
by using local method of Lyapunov –Schmidt .
The reduced equation has been found as a
system of nonlinear algebraic equations . We
gave a Geometric description of The
Discriminate set with the spreading of the
regular solutions of a specified system.

: Solving transportation problems where products to be supplied from one side(sources) to
another (demands) with a goal to minimize the overall transportation cost represents an activity of great
importance. Most of the works done in the field deals with the problem as two-sided model (Sources such
as factories and Demands such as warehouses) with no connections between sources or demands.
However, real world transportation problems may come in another model where sources are connected in
a network like graph in which each source may supply other sources in a specific cost. The work in this
paper suggests an algorithm and a graph model with mathematical solution for finding the minimum
feasible solution for such widely used transportation problems. In this work, the graph representing the
problem in which all sources are connected together in a network model with specific cost on each edge is
converted into a new graph where additional virtual sources representing supplies between sources are
added to the graph , new costs between the added sources and the demands are also calculated, and then
modified Kruskal’s algorithm is applied to get the minimum feasible solution.
The proposed solution is a straight forward model with strong mathematical and graph models. It can be
widely used for solving real world transportation problems with feasible time and space complexity where
time complexity of O(E2 + V2
) is required, where E represents the number of edges and V represents the
number of vertices. Different numerical examples were used to study the effectiveness and correctness of
the proposed algorithm.

A new three-term conjugate gradient
algorithm for training feed-forward neural
networks is developed. It is a vector based
training algorithm derived from DFP quasiNewton and has only O(n) memory. The global
convergence to the proposed algorithm has
been established for convex function under
Wolfe condition. The results of numerical
experiments are included and compared with
other well known training algorithms in this
field.

Let be a topological
space, let be an M-structure on
then is called a minimal
bitopological space. In this work, I
am study pre-open sets in minimal
bitopological spaces with some
result and definitions separation
axioms on minimal bitopological
with study some fundamental of
their properties.

The aim of this paper is to use TakagiSugeno-Kang(zero-order) model as
fuzzy neural network for the medical
diagnosis of hepatitis diseases which
represent a major public health problem all
around the world . For further improve the
accuracy and the speed of the diagnosis,
the Microarray Attribute Reduction
Scheme (MARS) for reduction features (or
attributes) and Mean Imputation (MI)
method for treatment the missing values
were used in this work. The used data
source of hepatitis diseases was taken
from UCI machine learning repository.
After treat the missing values problem
by apply MI method, the dataset is
partitioned into three training–testing
partitions (30%–70%, 40–60% and 20%–
80% respectively) and apply MARS with
different values of thr(from 0.1-0.9 ) in
order to determine the number attributes
(that represent the number of inputs to the
fuzzy neural network), the results record in
each case of thr values and each case of
partitions. The high diagnosis accuracy
has been achieved for the 40–60%
training–testing, namely, 100% for
training and 95.77% for testing with thr
equal to 0.4 and with less training cycle
and fuzzy sets number. This work was
implemented in MATLAB 7.0
environment.

In this paper, we introduce and study a new
class of meromorphic Univalent functions
defined by Dziok_Srivastava operator for this
class. We obtain coefficient inequality, convex
set, closure and Hadamard product (or
convolution).Further we obtain a -
neighborhood of the function , and the
integral transform.