Table 2 The parameter settings for the relevant methods

LFOA

ax, ay

20,20

bx, by

10,10

FOA

ax, ay

20,20

bx, by

10,10

GA

crossover

0.4

mutation

0.01

PSO

c ₁ , c ₂

2

w

1

v _max

6

MFO

a

a∈[−1–2]

b

1

BA (bat algorithm)

Q

Q∈[0 2]

A

0.5

r

0.5

DA (dragon fly algorithm)

w

w∈[0.9 0.2]

s

0.1

a

0.1

c

0.7

f

1

e

1

FPA (flower pollination algorithm)

p

0.8

λ

1.5

SCA (sine cosine algorithm)

a

2

RF

Number of trees (ntree)

500

Number of variables (mtry)

3

BPNN

Number of hidden neurons

8

Type of activation function

Sigmoid

Learning algorithm

tranlim

ELM

Number of hidden neurons

50

Type of activation function

Sigmoid