22,31,44,29,12,19,11,43,23

Target: 3 from 9.

Good Luck,

Evil Nigel

--- SoupGate-Win32 v1.05
* Origin: fsxNet Usenet Gateway (21:1/5)

35 38 41 33 28 20 26 36

target: 3 in 8

Nan

--- SoupGate-Win32 v1.05
* Origin: fsxNet Usenet Gateway (21:1/5)

33 28 46 21 38 26 36 35
Target: 3 or 4 in 8
Nan

--- SoupGate-Win32 v1.05
* Origin: fsxNet Usenet Gateway (21:1/5)

more sets to be tested


31, 36, 37, 21,8,23,57,55,

32, 33, 40, 15,7,26,57,54,

29, 31, 33, 17,13,19,54,48,

32, 34, 37, 14,8,21,58,52,

33, 40, 41, 21,10,22,57,51,

31, 33, 36, 11,5,19,56,53,

Target: 3 in 8
Nan

--- SoupGate-Win32 v1.05
* Origin: fsxNet Usenet Gateway (21:1/5)

target 3 in 8
21, 36,7,27,37,46,3,28,

11 21,5,14,23,43,2,16

8 26,5,10,27,34,4,18

13 28,8,18,32,43,1,24

10 22,7,13,28,40,3,16

14 29,5,18,33,43,2,24

13 33,9,14,36,46,4,23

19 33,7,26,36,45,3,29
Nan

--- SoupGate-Win32 v1.05
* Origin: fsxNet Usenet Gateway (21:1/5)

All tests are generated by random.org following the principle as below:

If a set of random numbers has as many lottery numbers from the previous draw as possible, it is more likely that the set will have as many lottery numbers for the most future draw.

The final 8 numbers are chosen with a random pattern from 16 numbers.

Nan

--- SoupGate-Win32 v1.05
* Origin: fsxNet Usenet Gateway (21:1/5)

王乾懿 Wang Qianyi (Nan) wrote:

35 38 41 33 28 20 26 36

target: 3 in 8

Nan

Ha!

Good luck,

Evil Nigel

--- SoupGate-Win32 v1.05
* Origin: fsxNet Usenet Gateway (21:1/5)

The genetic method is used to select 8 integers from a set of 16. The effect will only be known once the results are released a few hours later.

A genetic algorithm is a type of randomized search strategy that emerged from biology's evolution law. To begin, some groups were randomly generated to form an initial population. Next, construct a set of candidate problem solutions using the fitness
function determined by the objective function. Finally, the fitness of each individual to the problem environment is calculated using the fitness function determined by the objective function.

Individuals are then chosen based on their fitness, low fitness individuals are inhibited, high fitness individuals are left, and crossover and mutation operations are performed to produce an evolved generation of groups, so that repeated operations
continue to evolve towards the optimal solution from generation to generation.

Finally, select the group that meets the convergence conditions and is best suited to the problem environment, resulting in the problem's optimal solution.

Nan

--- SoupGate-Win32 v1.05
* Origin: fsxNet Usenet Gateway (21:1/5)

在 2022年1月12日星期三 UTC+8 23:35:01，<nigel> 写道：

王乾懿 Wang Qianyi (Nan) wrote:

35 38 41 33 28 20 26 36

target: 3 in 8

Nan

Ha!

Good luck,

Evil Nigel

Hopefully, the tests will perform well to prove my theory works somehow.

Nan

--- SoupGate-Win32 v1.05
* Origin: fsxNet Usenet Gateway (21:1/5)

[[7, 31, 46, 12, 56, 29, 53, 3, 36, 5, 43, 52, 33, 28, 25, 21],
[31, 45, 57, 21, 56, 3, 48, 15, 17, 46, 7, 41, 29, 43, 13, 28],
[33, 43, 21, 56, 29, 52, 37, 14, 36, 46, 58, 20, 28, 41, 50, 57],
[57, 21, 33, 31, 41, 8, 43, 37, 28, 5, 46, 3, 34, 2, 11, 56],
[18, 16, 21, 28, 6, 7, 33, 57, 36, 37, 31, 46, 3, 43, 56, 14]]

--- SoupGate-Win32 v1.05
* Origin: fsxNet Usenet Gateway (21:1/5)

Congrats on NN and Nan!
The method is working now.

Winning Numbers
08* 21* 37* 39* 56* 59* + 32

22,31,44,29,12,19,11,43,23

Target: 3 from 9.

Good Luck,

Evil Nigel
Loss 84 euro
Nan
35 38 41 33 28 20 26 36
target: 3 in 8
Loss 56 euro
33 28 46 21* 38 26 36 35
Target: 3 or 4 in 8
Loss 56 euro

more sets to be tested
31, 36, 37*, 21*,8*,23,57,55,
Winning 800-56=744 euro
32, 33, 40, 15,7,26,57,54,
Loss 56 euro
29, 31, 33, 17,13,19,54,48,
Loss 56 euro
32, 34, 37*, 14,8*,21*,58,52,
Winning 800-56=744 euro

33, 40, 41, 21*,10,22,57,51,
Loss 56 euro

31, 33, 36, 11,5,19,56*,53,
Loss 56 euro

Target: 3 in 8
target 3 in 8
21*, 36,7,27,37*,46,3,28,
Loss 56 euro

11 21*,5,14,23,43,2,16
Loss 56 euro
8* 26,5,10,27,34,4,18
Loss 56 euro
13 28,8*,18,32,43,1,24
Loss 56 euro
10 22,7,13,28,40,3,16
Loss 56 euro
14 29,5,18,33,43,2,24
Loss 56 euro
13 33,9,14,36,46,4,23
Loss 56 euro
19 33,7,26,36,45,3,29
Loss 56 euro
Toally winning: (2*800)-(56*16)=704 euro
Bravo!

NN
[[7, 31, 46, 12, 56*, 29, 53, 3, 36, 5, 43, 52, 33, 28, 25, 21*],
Loss
[31, 45, 57, 21*, 56*, 3, 48, 15, 17, 46, 7, 41, 29, 43, 13, 28],
Loss 560 euro
[33, 43, 21*, 56*, 29, 52, 37*, 14, 36, 46, 58, 20, 28, 41, 50, 57],
Loss 560 euro
[57, 21*, 33, 31, 41, 8*, 43, 37*, 28, 5, 46, 3, 34, 2, 11, 56*],
Winning (800*4)-560=2640 euro
[18, 16, 21*, 28, 6, 7, 33, 57, 36, 37*, 31, 46, 3, 43, 56*, 14]]
Winning (800-560)=240 euro
Totally winning: (2640+240)-(560+560)=1760 euro

--- SoupGate-Win32 v1.05
* Origin: fsxNet Usenet Gateway (21:1/5)

We share the same prize ratio too.

Nan
(2*800)/(56*16)=178.57%
NN
(5*800)/(4*560)=178.57%

Nan

--- SoupGate-Win32 v1.05
* Origin: fsxNet Usenet Gateway (21:1/5)