& performance analysis :
objectives are to minimize the flowrate
F of experimental process control setup
by choosing optimal design variables: the Anemometer flowsensor output
x(1), pipe diameter x(2) , liquid
conductivity x(3) and the liquid viscosity x(4).This objective design problem can be written as :
is worth to pointing out the minimum
value of the objective function . In this paper FPA has to be extended in
combination with constraint handling techniques to deal with mixed integer
problems efficiently under the simplest branch-and -bound method utilized here.
execute for solving the non linear equation in FPA , we get the co efficient of x(1), x(2),x(3) & x(4)
& e ,
co efficient :
1.6563 0.6446 9.9035
and total error
is For 5.3291e-05(fmin) difference between the predicted & the optimized output.
using Flower Pollination Alogorithm method and ANOVA we obtained the a
significant different result of optimum
conditions.The following are the co efficient of the parameters in order of
significantly affecting the liquid flow process : sensor output x(1) ,pipe
diameter x(2),liquid conductivity x(3) & liquid viscosity x(4) are (14.20 ,-4.37947,-12.94,2.94 &.350099*10^-3)in ANOVA
& new set of value coffeicient in FPA is (1.6563, 0.6446 , 9.9035 , -0.1291 & 50).Both the cases The predicted result
is compared to the experiments ,verified.
Therefore the obtained optimum conditions are proven to be effective. The
optimization process that performed by FPA method brings out the best conditions to be
used in a liquid flow process that could actualize a friendly environmental
process due to the total least error.