Abstracts Book - IMRC 2018

• SB2-O001
OPTIMIZATION OF NANOFILTRATION USING ARTIFICIAL NEURAL
NETWORKS
Belkis Sulbaran 1 , Kelly Joel Gurubel Tun 2 , Abigail Eloisa Madrigal Olvera 2 , Virgilio Zuñiga
Grajeda 3
1
Universidad de Guadalajara, Departamento de Estudios de Agua y Energía, Mexico.
2 Universidad de Guadalajara, Departamento de Estudios del Agua y la Energía, Mexico.
3 Universidad de Guadalajara, Departamento de Ciencias de la Información y Desarrollos
Tecnológicos, Mexico.
Membrane systems have been widely used in various processes such as in the
field of pharmaceutical chemistry, fine chemicals and food production. These
devices are associated with expensive and unwieldy processes. Therefore, a lot
of studies were developed with the aim of improving the efficiency and control
of these processes using filtration. Evolutionary algorithms are stochastic
optimization methods that have been developed as a combination of rules and
randomness that seeks to imitate different natural phenomena as animal
behavior or physical laws. An important feature of evolutionary methods is that
their operation is based on the analysis of candidate solutions that are randomly
initialized, while every step of optimization is developed better solutions to
regions in space of the task. Different operators derived the analogy of every
evolutionary approach is applied to each candidate solution to ensure that each
step, such solutions to better approximate that required to meet an objective
function solution. One way to find the optimized parameters is to obtain a
mathematical model. This model can be obtained using a technique called
artificial neural networks which is a computational representation of a set of
neural units or artificial neurons that mimic the way a biological brain learns and
solves problems based on previous experiences. Accordingly in this study it is
proposed to use these methods to optimize the design for manufacturing
nanostructured cellulose membranes, with optimization are expected to find
the most suitable conditions for manufacturing in order to find that are low cost
and potential for various applications.
Keywords: cellulose acetate, optimization, nanofiltration
Presenting authors email: sulbaranbelkis7@gmail.com