Theatre Booking System Lesson 3
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The document discusses inserting random numbers using the RANDBETWEEN formula to test a theatre booking system model. It explains that the RANDBETWEEN formula generates random numbers between the bottom and top numbers specified, in this case 0 and 4, to represent randomly booked seats. It also provides instructions to enable the Analysis ToolPak add-in if the RANDBETWEEN function does not work initially, and how to copy the formula down and across cells to populate the model with random seat bookings for testing.
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Write a program that inputs 10 integers from the user into an array, and removes the duplicate array elements. By removing, I meant that you
should make it appear as if the elements hadn't been there. So not just setting duplicates to an "empty" value, but filling in the gap. That means
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0 1 2 3 4 5 6 7 8 9
Program Output:
Please enter 10 integers, hitting return after each one: \n
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Program Input:
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I have:
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using namespace std;
void eliminate(int a[], int& siz)
{
int i,n=0;
bool b[101]={false};
for(i=0;i<siz;i++)
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siz=n;
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{
int nums[10];
int i,n=10;
cout<<"Please enter 10 integers, hitting return after each one: \n";
for(i=0;i<n;i++)
cin>>nums[i];
eliminate(nums,n);
cout<<endl;
for(i=0;i<n;i++)
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return 0;
}
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Please look at the problems I am having which are listed below: Write a prog...
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Write a program that inputs 10 integers from the user into an array, and removes the duplicate array elements. By removing, I meant that you
should make it appear as if the elements hadn't been there. So not just setting duplicates to an "empty" value, but filling in the gap. That means
moving all the later elements back one (kind of like when you hit backspace in the middle of a line in a text editor). Or alternatively, storing only the
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pass an array into that function as a parameter.
Output should look exactly like below. Two rows.
Program Input:
0 1 2 3 4 5 6 7 8 9
Program Output:
Please enter 10 integers, hitting return after each one: \n
0 1 2 3 4 5 6 7 8 9
Program Input:
100 100 100 100 100 100 100 100 100 100 100
Program Output:
Please enter 10 integers, hitting return after each one: \n
100
Program Input:
11 11 22 22 33 33 44 44 55 55
Program Output:
Please enter 10 integers, hitting return after each one: \n
11 22 33 44 55
Program Input:
12 37 12 37 45 88 101 21 21 101
Program Output:
Please enter 10 integers, hitting return after each one: \n
12 37 45 88 101 21
I have:
#include<iostream>
using namespace std;
void eliminate(int a[], int& siz)
{
int i,n=0;
bool b[101]={false};
for(i=0;i<siz;i++)
b[a[i]]=true;
for(i=0;i<101;i++)
if(b[i]) a[n++]=i;
siz=n;
}
int main()
{
int nums[10];
int i,n=10;
cout<<"Please enter 10 integers, hitting return after each one: \n";
for(i=0;i<n;i++)
cin>>nums[i];
eliminate(nums,n);
cout<<endl;
for(i=0;i<n;i++)
cout<<nums[i]<<" ";
return 0;
}
--- PROBLEMS I AM HAVING ---
1) After, cout<<"Please enter 10 integers, hitting return after each one: \n"; I receive 2 "/n" how do I only receive one "\n" after the colon.
2) For my last output, I receive 12 12 21 37 45 88 when I should be receiving 12 37 45 88 101 21
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- Desirable properties for random number generators including being fast, requiring little memory, having a long cycle or period, and producing numbers that are close to uniform and independent.
Random number generator
This document discusses random number generators and reviews Intel's random number generator. It begins with an introduction to random number generation and common pseudorandom number generators like linear congruential generators. It then describes Intel's true random number generator which uses thermal noise from resistors to modulate the frequency of an oscillator. The random bits generated from the clock drift are then processed digitally before being made available through Intel's software library. Empirical and theoretical tests for evaluating random number generators are also summarized.
Pseudorandom number generators powerpoint
This document summarizes and tests four different pseudorandom number generators. Generator 1, which uses modular exponentiation, produces well-distributed numbers and differences but is too computationally intensive. Generator 2, which uses a sine wave function, generates numbers that are clustered on the sides and has differences centered around 0. Generator 3, which uses exponential functions, has near-perfect number distribution but a limited difference range of two values. Generator 4, based on logarithms, fails to produce a consistent distribution and has differences that converge to a single value. In conclusion, creating effective pseudorandom number generators is very challenging.
Random Number Generation
This document discusses tests for random number generation, including the autocorrelation test, gap test, and poker test. The autocorrelation test examines dependence between numbers in a sequence. The gap test analyzes the length of gaps between numbers that fall within a given range. The poker test categorizes groups of five consecutive numbers based on arrangements like pairs, three of a kind, etc. and applies a chi-squared test to assess randomness.
Pseudo Random Number Generators
This presentation on Pseudo Random Number Generator enlists the different generators, their mechanisms and the various applications of random numbers and pseudo random numbers in different arenas.
Random number generation
This document discusses random number generation and properties of pseudo-random numbers. It covers techniques for generating pseudo-random numbers like linear congruential methods and combined congruential methods. It also discusses hypothesis tests that can be used to test for uniformity and independence of random numbers, such as the frequency test, Kolmogorov-Smirnov test, chi-square test, runs test, and autocorrelation test.
Generate and test random numbers
This document discusses methods for generating and testing random numbers. There are two main types of random number generators discussed: combined generators and inversive generators. Combined generators work by combining the outputs of two or more simpler random number generators. They are useful for simulating highly reliable systems or complex networks. The document also discusses how to test random numbers using the Kolmogorov-Smirnov test and runs tests. The Kolmogorov-Smirnov test compares the cumulative distribution function of observed values to expected values, while runs tests examine the arrangements of values in a sequence. Both can be used to determine if a random number generator is producing independent and identically distributed values.
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another program like it. All you have to is input the data into the table, and then click on an
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
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- 1. Theatre Booking System Lesson 3: Inserting random numbers to test your model
- 2. We are going to enter a formula called =Randbetween(bottom,top) This allows the computer to generate random numbers between the two numbers we specify. Why are you going to use the numbers 0 and 4?
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