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radaar

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Three level Newton-Raphson optimization ...

radaar 202 Maple
optimization numeric newton
September 04 2020
1 3

Newton raphson method is used for optimization of functions and is based on taylor series expansion. Here is the code for a three level newton raphson method.
 

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restart; with(Student[MultivariateCalculus]); ff := proc (xx) xx^3-2*xx+2 end proc; ii := 0; XX[ii] := 2; while ii < 25 do GR := Gradient(ff(xx), [xx] = [XX[ii]]); GR1 := evalf(GR[1]); HESS := Student[VectorCalculus]:-Hessian(ff(xx), [xx] = [XX[ii]]); HESS1 := evalf(HESS[1]); YY[ii] := XX[ii]-GR1[1]/HESS1[1]; GR := Gradient(ff(xx), [xx] = [YY[ii]]); GR1 := evalf(GR[1]); HESS := Student[VectorCalculus]:-Hessian(ff(xx), [xx] = [YY[ii]]); HESS1 := evalf(HESS[1]); ZZ[ii] := YY[ii]-GR1[1]/HESS1[1]; GR := Gradient(ff(xx), [xx] = [ZZ[ii]]); GR1 := evalf(GR[1]); HESS := Student[VectorCalculus]:-Hessian(ff(xx), [xx] = [ZZ[ii]]); HESS1 := evalf(HESS[1]); ii := ii+1; XX[ii] := ZZ[ii-1]-GR1[1]/HESS1[1]; printf("%a\n", XX[ii]) end do

.8180854533
.8164965808
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ff(.8164965808)

.911337892

 (1)
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with(Optimization); Minimize(xx^3-2*xx+2, xx = -2 .. 2)

[HFloat(0.9113378920963653), [xx = HFloat(0.8164965785244629)]]

 (2)
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NULL


 

Download THREE_LEVEL_NEWTON_RAPHSON_METHOD1.mw

Monte Carlo Integration...

radaar 202 Maple
integration montecarlo numeric
June 15 2020
1 1

Monte Carlo integration uses random sampling unlike classical techniques like the trapezoidal or Simpson's rule in evaluating the integration numerically.

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restart; ff := proc (rho, phi) return exp(rho*cos(phi))*rho end proc; aa := 0; bb := 1; cc := 0; dd := 2*Pi; alfa := 5; nrun := 15000; sum1 := 0; sum2 := 0; X := Statistics:-RandomVariable(Uniform(0, 1)); SX := Statistics:-Sample(X); for ii to nrun do u1 := SX(1)[1]; u2 := SX(1)[1]; xx1 := aa+(bb-aa)*u1; xx2 := cc+(dd-cc)*u2; xx3 := (bb-aa)*(1-u1); xx4 := (dd-cc)*(1-u2); sum1 := sum1+evalf(ff(xx1, xx2)); sum2 := sum2+evalf(ff(xx1, xx2))+evalf(ff(xx1, xx4))+evalf(ff(xx3, xx2))+evalf(ff(xx3, xx4)) end do; area1 := (bb-aa)*(dd-cc)*sum1/nrun; area2 := (bb-aa)*(dd-cc)*sum2/(4*nrun); area2

HFloat(3.5442090450428574)

 (1)
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evalf(Int(exp(rho*cos(phi))*rho, rho = 0 .. 1, phi = 0 .. 2*Pi))

3.550999378

 (2)
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NULL


 

Download MONTE_CARLO_INTEGRATION1.mw

 

 

Binary Search Algorithm...

radaar 202 Maple
array index
February 29 2020
1 4

The binary search algorithm is used to obtain the index of a given number by dividing the search bound in half over iteration. If the value entered in the array a message pop up telling that ''value is not present in the array". Please see the code. 
 

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restart; with(ArrayTools); AA := Array(1 .. 10, [20, 2, 30, 4, 50, 7, 60, 8, 90, 100]); AA := sort(AA); KEYVALUE := 200; DUP_KEYVALUE := infinity; low := 1; high := NumElems(AA); while DUP_KEYVALUE <> KEYVALUE do mid := floor((low+high)*(1/2)); if AA[mid] = KEYVALUE then DUP_KEYVALUE := KEYVALUE; printf("%s\n %a\n", "the index is ", mid) elif AA[mid] < KEYVALUE then low := mid+1 elif AA[mid] > KEYVALUE then high := mid-1 end if; if low > high then printf("%s\n", "value not present in the array"); break end if end do


 

Download BINARY_SEARCH1.mw

 

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