1answer.
Ask question
Login Signup
Ask question
All categories
  • English
  • Mathematics
  • Social Studies
  • Business
  • History
  • Health
  • Geography
  • Biology
  • Physics
  • Chemistry
  • Computers and Technology
  • Arts
  • World Languages
  • Spanish
  • French
  • German
  • Advanced Placement (AP)
  • SAT
  • Medicine
  • Law
  • Engineering
disa [49]
3 years ago
6

Evaluate the expression (x^5)^3(16x^8)^1/2

Mathematics
1 answer:
Contact [7]3 years ago
3 0

Answer:

8x^23 i think

You might be interested in
What is the solution to the equation P over 9= 72?
Fed [463]
P / 9 = 72

Multiply both sidess by 9

P / 9 (9) = 72 (9)

p = 648

4 0
3 years ago
Isabella invited some friends to her birthday party, but a few weren't able to attend. Of the friends she invited, 8 attended. T
LuckyWell [14K]

Answer:

80% or like 8 squares out of 10 oe=r 4 out of 5 ect

Step-by-step explanation:

5 0
2 years ago
Read 2 more answers
Write the function in standard form <br><br> F(x)=-3(x-6)^2+15
LenKa [72]

Answer:

(6,15)

Step-by-step explanation:

7 0
3 years ago
PLEASE HURRY I NEED YOUR HELP! show work
8090 [49]

Answer:

1) 10

- 3 3/8

________

=6 5/8

2)  1/5= 2/10

2/10

+ 20 3/10

+ 5 6/10

_________

25 11/10

= 26 1/10

3) 11/12

+ 10

- 10/12

________

= 10 1/12

5 0
3 years ago
Provide an example of optimization problem
Mashutka [201]

Answer:

a. Convex solutions ,GO Methods

b. market efficiency

Explanation :

Step-by-step explanation:

A globally optimal solution is one where there are no other feasible solutions with better objective function values. A locally optimal solution is one where there are no other feasible solutions "in the vicinity" with better objective function values. You can picture this as a point at the top of a "peak" or at the bottom of a "valley" which may be formed by the objective function and/or the constraints -- but there may be a higher peak or a deeper valley far away from the current point.

In convex optimization problems, a locally optimal solution is also globally optimal. These include LP problems; QP problems where the objective is positive definite (if minimizing; negative definite if maximizing); and NLP problems where the objective is a convex function (if minimizing; concave if maximizing) and the constraints form a convex set. But many nonlinear problems are non-convex and are likely to have multiple locally optimal solutions, as in the chart below. (Click the chart to see a full-size image.) These problems are intrinsically very difficult to solve; and the time required to solve these problems to increases rapidly with the number of variables and constraints.

GO Methods

Multistart methods are a popular way to seek globally optimal solutions with the aid of a "classical" smooth nonlinear solver (that by itself finds only locally optimal solutions). The basic idea here is to automatically start the nonlinear Solver from randomly selected starting points, reaching different locally optimal solutions, then select the best of these as the proposed globally optimal solution. Multistart methods have a limited guarantee that (given certain assumptions about the problem) they will "converge in probability" to a globally optimal solution. This means that as the number of runs of the nonlinear Solver increases, the probability that the globally optimal solution has been found also increases towards 100%.

Where Multistart methods rely on random sampling of starting points, Continuous Branch and Bound methods are designed to systematically subdivide the feasible region into successively smaller subregions, and find locally optimal solutions in each subregion. The best of the locally optimally solutions is proposed as the globally optimal solution. Continuous Branch and Bound methods have a theoretical guarantee of convergence to the globally optimal solution, but this guarantee usually cannot be realized in a reasonable amount of computing time, for problems of more than a small number of variables. Hence many Continuous Branch and Bound methods also use some kind of random or statistical sampling to improve performance.

Genetic Algorithms, Tabu Search and Scatter Search are designed to find "good" solutions to nonsmooth optimization problems, but they can also be applied to smooth nonlinear problems to seek a globally optimal solution. They are often effective at finding better solutions than a "classic" smooth nonlinear solver alone, but they usually take much more computing time, and they offer no guarantees of convergence, or tests for having reached the globally optimal solution.

5 0
3 years ago
Other questions:
  • Drag each equation show if it could be a correct first step to solving the equation. 4(3+x)=36.
    12·2 answers
  • What is -1.3 ≥ 2.9 -0.6r graph the solution
    10·1 answer
  • There are 5,280 feet in one mile . How many inches are in 3.2 miles
    15·2 answers
  • On a test I was given 2 triangles. One triangle gave measurements of all three sides as 2, 4, and 5. The next triangle had sides
    8·1 answer
  • Rational expressions always contain logarithms. 1) Always true 2) Never true 3) Sometimes true
    6·1 answer
  • Which statement correctly describes a line graph?
    5·1 answer
  • Can you plz help me with this I'm confused
    6·1 answer
  • Jose Rodriguez recently sold 1,320 shares of oil stock for $31.70 per share plus a commission of $29.95 plus $0.03 per share. He
    11·1 answer
  • Solve this A tourist starts off from town A and travels for 50km on a bearing of N80°W to town B.At town B ,he continues for ano
    10·1 answer
  • I need help?? I don’t understand thanks!!
    8·1 answer
Add answer
Login
Not registered? Fast signup
Signup
Login Signup
Ask question!