Table 3 Parameters settings.

From: Hybrid rice optimization algorithm inspired grey wolf optimizer for high-dimensional feature selection

Algorithms

Parameters

Settings

Termination criteria

PSO

\(c_1\), \(c_2\)

2

Number of iterations = 1000

(\(w_{min}\), \(w_{max}\))

(0.2, 0.9)

SCA

a

2

WOA

a

Linearly decreasing from 2 to 0

p

Random value from 0 to 1

l

Random vector from -1 to 1

HRO

\(SC_{max}\)

60

GWO

a

Linearly decreasing from 2 to 0

I-GWO

a

Linearly decreasing from 2 to 0

MSGWO1

a

Linearly decreasing from 2 to 0

MSGWO2

a

Linearly decreasing from 2 to 0

HO

\(\vartheta\)

1.5

IVYA

\(\beta\)

Random value from 1 to 1.5

HRO-GWO

\(\varepsilon\)

4

\(\omega\)

0.01

\(C_{R1}\)

0.8

\(C_{R2}\)

0.3