logical riddle 9+7

Description

2+3=10 7+2=63 6+5=66 8+4=96 9+7=?

Inputs

  • 2
  • 3

Outputs

  • 10

Neuron type

Best algorithm has been found - locked

Patterns

Pattern Input Output
1.
2: 2
3: 3
10: 10
2.
2: 7
3: 2
10: 63
3.
2: 6
3: 5
10: 66
4.
2: 8
3: 4
10: 96

Applicable neurons

  • Plus (x + y)
  • Minus (x - y)
  • Multiple (x × y)
  • Division (x ÷ y)
  • Absolute value
  • Half of number
  • is it even?
  • character i
  • character (
  • \\n
  • Half of number
  • Width of persons

Algorithm

Test

Code made by AI:
/**
 * 2: 
 *
 * @return {Array}
 */
function neuron502()
{
return [2];
}

/**
 * Division (x ÷ y): X / Y
 *
 * @param x1 first number
 * @param x2 second number
 * @return {Array}
 */
function neuron17(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '/'+Number(x2)).toString()];
}

/**
 * Round to an integer: round(x)
 *
 * @param x1 Value
 * @return {Array}
 */
function neuron620(x1)
{
return[Math.round(Number(x1))]
}

/**
 * a = b: IF a=b THEN 1 ELSE 0;
 *
 * @param x1 a
 * @param x2 b
 * @return {Array}
 */
function neuron591(x1, x2)
{
return [(x1 == x2) ? 1 : 0];
}

/**
 * is it even?: 
 * 
 * @param x1 Number
 * @return {Array}
 */
function neuron848(x1)
{
  var outputs = [];
  outputs[0] = x1;

  arr = neuron502();
  outputs[1] = arr[0];

  arr = neuron17(outputs[0], outputs[1]);
  outputs[2] = arr[0];

  arr = neuron620(outputs[2]);
  outputs[3] = arr[0];

  arr = neuron591(outputs[2], outputs[3]);
  outputs[4] = arr[0];

  return[outputs[4]];
}


/**
 * Plus (x + y): The addition of two whole numbers is the total amount of those quantities combined.
 *
 * @param x1 first number
 * @param x2 second number
 * @return {Array}
 */
function neuron1(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '+'+Number(x2)).toString()];
}

/**
 * Multiple (x × y): 
 *
 * @param x1 Number X
 * @param x2 Number Y
 * @return {Array}
 */
function neuron3(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '*'+Number(x2)).toString()];
}

/**
 * Division (x ÷ y): X / Y
 *
 * @param x1 first number
 * @param x2 second number
 * @return {Array}
 */
function neuron17(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '/'+Number(x2)).toString()];
}

/**
 * 5: 
 *
 * @return {Array}
 */
function neuron505()
{
return [5];
}

/**
 * character .: 
 *
 * @return {Array}
 */
function neuron510()
{
return['.'];
}

/**
 * Connect - two inputs: 
 *
 * @param x1 Variable A
 * @param x2 Variable B
 * @return {Array}
 */
function neuron520(x1, x2)
{
return [x1.toString()+x2.toString()];
}

/**
 * Half (0.5): 
 * 
 * @return {Array}
 */
function neuron522()
{
  var outputs = [];

  arr = neuron505();
  outputs[0] = arr[0];

  arr = neuron510();
  outputs[1] = arr[0];

  arr = neuron520(outputs[1], outputs[0]);
  outputs[2] = arr[0];

  return[outputs[2]];
}


/**
 * Multiple (x × y): 
 *
 * @param x1 Number X
 * @param x2 Number Y
 * @return {Array}
 */
function neuron3(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '*'+Number(x2)).toString()];
}

/**
 * Half of number: 
 * 
 * @param x1 Number
 * @return {Array}
 */
function neuron845(x1)
{
  var outputs = [];
  outputs[0] = x1;

  arr = neuron522();
  outputs[1] = arr[0];

  arr = neuron3(outputs[0], outputs[1]);
  outputs[2] = arr[0];

  return[outputs[2]];
}


/**
 * Multiple (x × y): 
 *
 * @param x1 Number X
 * @param x2 Number Y
 * @return {Array}
 */
function neuron3(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '*'+Number(x2)).toString()];
}

/**
 * x to the 2 (x²): x squared
 * 
 * @param x1 Number X
 * @return {Array}
 */
function neuron7(x1)
{
  var outputs = [];
  outputs[0] = x1;

  arr = neuron3(outputs[0], outputs[0]);
  outputs[1] = arr[0];

  return[outputs[1]];
}


/**
 * 5: 
 *
 * @return {Array}
 */
function neuron505()
{
return [5];
}

/**
 * character .: 
 *
 * @return {Array}
 */
function neuron510()
{
return['.'];
}

/**
 * Connect - two inputs: 
 *
 * @param x1 Variable A
 * @param x2 Variable B
 * @return {Array}
 */
function neuron520(x1, x2)
{
return [x1.toString()+x2.toString()];
}

/**
 * Half (0.5): 
 * 
 * @return {Array}
 */
function neuron522()
{
  var outputs = [];

  arr = neuron505();
  outputs[0] = arr[0];

  arr = neuron510();
  outputs[1] = arr[0];

  arr = neuron520(outputs[1], outputs[0]);
  outputs[2] = arr[0];

  return[outputs[2]];
}


/**
 * x to the a  (xª): value of the number x to be the power of a
 *
 * @param x1 x - The base
 * @param x2 a - The exponent
 * @return {Array}
 */
function neuron18(x1, x2)
{
return[Math.pow(Number(x1), Number(x2))];
}

/**
 * Square root (√¯): 
 * 
 * @param x1 Number X
 * @return {Array}
 */
function neuron554(x1)
{
  var outputs = [];
  outputs[0] = x1;

  arr = neuron522();
  outputs[1] = arr[0];

  arr = neuron18(outputs[0], outputs[1]);
  outputs[2] = arr[0];

  return[outputs[2]];
}


/**
 * Absolute value: 
 * 
 * @param x1 Number
 * @return {Array}
 */
function neuron570(x1)
{
  var outputs = [];
  outputs[0] = x1;

  arr = neuron7(outputs[0]);
  outputs[1] = arr[0];

  arr = neuron554(outputs[1]);
  outputs[2] = arr[0];

  return[outputs[2]];
}


/**
 * logical riddle 9+7: 2+3=10
7+2=63
6+5=66
8+4=96
9+7=?
 * 
 * @param x1 2
 * @param x2 3
 * @return {Array}
 */
function neuron927(x1, x2)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;

  arr = neuron848(outputs[0]);
  outputs[2] = arr[0];

  arr = neuron1(outputs[0], outputs[1]);
  outputs[3] = arr[0];

  arr = neuron3(outputs[2], outputs[1]);
  outputs[4] = arr[0];

  arr = neuron3(outputs[3], outputs[0]);
  outputs[5] = arr[0];

  arr = neuron17(outputs[2], outputs[4]);
  outputs[6] = arr[0];

  arr = neuron3(outputs[4], outputs[5]);
  outputs[7] = arr[0];

  arr = neuron17(outputs[5], outputs[7]);
  outputs[8] = arr[0];

  arr = neuron17(outputs[3], outputs[8]);
  outputs[9] = arr[0];

  arr = neuron1(outputs[0], outputs[1]);
  outputs[10] = arr[0];

  arr = neuron845(outputs[6]);
  outputs[11] = arr[0];

  arr = neuron570(outputs[11]);
  outputs[12] = arr[0];

  return[outputs[5]];
}


Code made by AI:

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