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Optimization: Newton Raphson Method
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Newton Raphson Method Algorithm in C
#include<stdio.h>#include<conio.h>
#include<math.h>
#include<stdlib.h>
float myFun(float x);
int main()
{
float e = 0.01,a,aw = 0,bw = 1,Lw,b,x1,x2,fxa,fxb,fxz,z,j=0;
int i=1,k;
float x[100],dx[100],fdx[100],fddx[100];
x[1] = 1;
dx[1] = (x[i]*1)/100;
begin:
if(j<100)
{
dx[i] = (x[i]*1)/100;
fdx[i] = ((myFun(x[i] + dx[i])) - (myFun(x[i] - dx[i])))/(2*dx[i]);
fddx[i] = ((myFun(x[i] + dx[i])) - (2*myFun(x[i])) + (myFun(x[i] - dx[i])))/(dx[i]*dx[i]);
printf("\nf'(%d) = %.4f",i,fdx[i]);
printf("\nf''(%d) = %.4f",i,fddx[i]);
k = i+1;
x[k] = (x[i] - (fdx[i] / fddx[i]));
printf("\n\nf(%d) = %.4f",k,x[k]);
dx[k] = (x[k]*1)/100;
fdx[k] = ((myFun(x[k] + dx[k])) - (myFun(x[k] - dx[k])))/(2*dx[k]);
if (fdx[k] < 0)
{
fdx[k] = ((-1)*fdx[k]);
}
if (fdx[k] > e)
{
j = j + 1;
i = i + 1;
goto begin;
}
else
{
printf("\n\nf'(%d) = %.9f is Less than termination factor e = %.3f",k,fdx[k],e);
goto end;
}
}
end:
return 0;
}
float myFun(float x) {
float y;
y = ((x*x)+(54/x));
return y; // return statement
}
Output:
Newton Raphson Method |
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