Table 3 Description of used symbols.

From: Enhanced Grey Wolf Optimization (EGWO) and random forest based mechanism for intrusion detection in IoT networks

Symbol

Description

X

Position of each wolf

Xα, Xβ and Xδ

Position of three best wolves

Xp

Position of prey

D

Distance vector

A and C

Co-efficient controlling exploration and exploitation

a

A value that decreases from 2 to 0 over the span of several repetitions

r1​ and r2

Random values in the range [0, 1] used for adjusting A and C

X(t + 1)

Updated position of wolf for next iteration

N

The number of alternative responses.

P(i, j)

Initial position matrix of wolves, values of the parameters ‘i’ and ‘j’ range from 1 to N and 1 to D, respectively

wi

Total no. of wolves in a pack

XΩ

Position of the omega wolf, used in EGWO

X(α,d), X(β,d), X(δ,d) and X(Ω,d)

Dimension split of the best four wolves

split (x1, x2, x3, x4)

EGWO-specific split function to balance between top wolf positions (α, β, δ, and Ω) and improve search space coverage.

b

constant; its value varies between 0 to 2,

Stepb(x), d

binary steps in dimension “d”

rand[0,1]

Random values for probabilistic crossover and adaptive position adjustments.

A

Accuracy

C1​, C2​

Constants weighting accuracy and feature size in the fitness function