A Novel Hybrid Runge Kutta Optimizer with Support Vector Machine on Gene Expression Data for Cancer Classification

. 2023 May 3;13(9):1621. doi: 10.3390/diagnostics13091621

Algorithm 1 The RUN algorithm

1:
Input: Population size, Population initialization, and MaxIter of iterations.
2:
Output: The best Solution.
3:
Evaluate Objective Function using Equation (7).
4:
Calculate $y_{n + 1}$ using Equation (2).
5:
while Stop condition not met do
6:
for n = 1 ... N do
7:
Evaluate Objective Function using Equation (7).
8:
if $< 0.5$ then
9:
calculate $y_{n e w 2}$ using Equation (5)
10:
if $F (y_{n + 1} < F (y_{n e w 2}))$ then
11:
if rand < w then
12:
Calculate $y_{n e w 3}$ using Equation (6).
13:
if $F (y_{n + 1}) < F (y_{n e w 3})$ then
14:
$y_{n + 1} = y_{n e w 3}$
15:
end if
16:
end if
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else
18:
$y_{n + 1} = y_{n e w 2}$
19:
end if
20:
end if
21:
end for
22:
end while