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ankoles [38]
3 years ago
13

An ostrich can run at a rate of 50 miles in 60 minutes.At this rate,how long would it take an ostrich to run 15 miles?

Mathematics
1 answer:
just olya [345]3 years ago
3 0
If an ostrich can run 50 miles in one hour then he can run 12.5 miles in 15 minutes. 15 minutes is 1/4 of an hour. Multiply 50 by 0.25 = 15.
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Six sprinters are racing in a 100-meter dash. How many different ways can a gold, silver, and
horrorfan [7]

Answer:

Step-by-step explanation:

Explanation

6 sprinters are in a race. Any one of the 6 could win. None of them can win 2 medals. So the first result is 6

5 runners remain. The second medal goes to any one of the 5

4 runners remain after 1 of the 5 have been choosen.  Any one of the 4 could win.

Answer 6 * 5 * 4 = 120

There are 120 ways of awarding 3 medals to 6 people.

3 0
2 years ago
Miss Osborne is standing next to a tree at high noon the tree cast a 44 foot shadow and miss Osborne cast a 4 foot shadow how ta
Gwar [14]

Answer:ok soooo I did this last year but I don’t remember anymore

Step-by-step explanation:

3 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
The base of a triangle is 6 meters longer than the height of the triangle. If the area of the triangle is 108 square meters, wha
Nonamiya [84]

Answer:

36 meters

Step-by-step explanation:

A=1/2b×h

108sq. m=1/2.6m×h

both side canceling meter

h=2×108m/6

h=36m. answer

4 0
3 years ago
How do you solve #23?
scZoUnD [109]

Answer:

m= 67.5 and n=56.25

Step-by-step explanation:

  180-15=165

  165/2= 82.5

  90-15= 75

  75+75= 150

  180-150=30

  30+82.5= 112.5

  180- 112.5= 67.5

  m= 67.5

  180-67.5= 112.5

  112.5/2= 56.25

  n= 56.25

7 0
11 months ago
Read 2 more answers
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