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mote1985 [20]
3 years ago
12

Can someone help me please​

Mathematics
2 answers:
IgorLugansk [536]3 years ago
7 0

Answer:

\sf   \dfrac{{x}^{a \: (b - c)} }{ {x}^{b \: (a - c)} } \:  \div  \:  \bigg \lgroup   \dfrac{ {x}^{b} }{ {x}^{a} } \bigg \rgroup^{c}  \:  =  \: 1

\\

Now,

\sf   \dfrac{{x}^{ab \:  -  \: ac} }{ {x}^{ba \:  - \: b c} } \:  \div  \:  \bigg \lgroup   \dfrac{ ({x}^{b} )}{( {x}^{a}) } \bigg \rgroup^{c}  \:  =  \: 1

\\

\sf   \dfrac{{x}^{ab \:  -  \: ac} }{ {x}^{ba \:  - \: b c} } \:  \div  \:   \dfrac{ {x}^{bc} }{{x}^{ac} } \:  =  \: 1

\\

We know that, When sign change from division to multiplication we should do reciprocal of next number.

Therefore we get,

\sf   \dfrac{{x}^{ab \:  -  \: ac} }{ {x}^{ba \:  - \: b c} } \:   \times \:   \dfrac{ {x}^{ac} }{{x}^{bc} } \:  =  \: 1

\\

\sf   \dfrac{{x}^{ab \:  -  \:  \cancel {ac }\:  +  \:  \cancel{ac}} }{ {x}^{ba \:  - \: \cancel{ b c} \:  +  \:  \cancel{bc}} }  \:  =  \: 1

\\

\sf   \dfrac{{x} \:  ^{ \cancel{ab}} }{ {x} \: ^{\cancel{ba}} }  \:  =  \: 1

\\

\bigstar \: \:   \underline{ \boxed{\sf   x  \:  =  \: 1}} \: \:  \bigstar

\\

\huge\bf \dag \:   \gray{RHS = LHS} \:  \dag

\\

\large \star \:  \tt Hence, Verified  \: \star

ANEK [815]3 years ago
5 0

Step-by-step explanation:

kindly see attached picture

hope it helped you:)

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The owner of an office building is expanding the length and width of a parking lot by the same amount. The lot currently measure
Gnoma [55]

The best and most correct answer among the choices provided by your question is the second choice or letter B "20".

The current area is 120(80)=9600 and he want to expand it by 4400 so that the new area will be 9600+4400=14000 

14000=(120+x)(80+x) 

14000=9600+200x+x^2 

x^2+200x-4400=0 

x^2-20x+220x-4400=0 

x(x-20)+220(x-20)=0 

(x+220)(x-20)=0, since x is an increase it must be greater than zero so 

x=20ft 

(120+20)(80+20)=14000ft^2


I hope my answer has come to your help. Thank you for posting your question here in Brainly.

4 0
3 years ago
Read 2 more answers
How do you convert 17 cmon minute to miles an hour
eimsori [14]

Answer:

0.006 miles per hour

Step-by-step explanation:

We are given;

Speed in cm per minute ( 17 cm per min)

We are required to convert cm per minute to miles an hour

we need to know that;

1 miles = 160934 cm

1 hour = 60 minutes

We can convert 17 cm to miles and 1 minute to hours

17 cm = 17 ÷ 160934 cm

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1 minute = 1/60 hour

Therefore;

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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%.

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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.

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Does anyone know how to solve this?
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After finding b, you can use the Law of Sines to find angles A and C or use other forms of the Law of Cosines to find angles A and C.

Try it....

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Step-by-step explanation:

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