The application of Simulated Annealing Algorithm, Firefly Algorithm, Invasive Weed Optimization, and Shuffled Frog Leaping Algorithm for prediction of Water Quality Index
Feridon Ghadimi,
No information about this author
Saeed Zolfaghari Moghaddam
No information about this author
Research Square (Research Square),
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 10, 2025
Abstract
Groundwater
is
a
vital
resource
for
drinking
water,
agriculture,
and
industry
worldwide.
Effective
groundwater
quality
management
crucial
safeguarding
public
health
ensuring
ecological
sustainability.
Hydrogeochemical
data
modeling
widely
utilized
to
predict
using
various
approaches.
The
method
proposed
in
this
study
leverages
an
intelligent
model
combined
with
chemical
compositions.
Sampling
was
conducted
from
175
agricultural
wells
the
Arak
Plain.
By
utilizing
hydrogeochemical
performing
correlation
sensitivity
analyses,
key
compositions
were
identified:
Ca²⁺,
Cl⁻,
EC,
HCO₃⁻,
K⁺,
Mg²⁺,
Na⁺,
pH,
SO₄²⁻,
TDS,
NO₃⁻.The
predicted
Water
Quality
Index
(WQI)
values
composition
artificial
neural
network
(ANN)
model.
of
served
as
model’s
input,
while
WQI
treated
output.
To
enhance
ANN's
accuracy,
several
optimization
algorithms
used,
including:
Simulated
Annealing
Algorithm
(SAA),
Firefly
(FA),
Invasive
Weed
Optimization
(IWO),
Shuffled
Frog
Leaping
(SFLA).The
comparison
results
indicated
that
ANN-SAA
outperformed
other
models.
R²
MSE
predicting
training
data:
=
0.8275,
0.0303
test
0.7357,
0.0371.These
demonstrate
provides
reliable
accurate
index
values,
offering
valuable
tool
assessment
management.
Language: Английский
Assessment of groundwater quality for irrigation using a new customized irrigation water quality index
Oualid Boukich,
No information about this author
Rihab Ben-tahar,
No information about this author
Mohamed Brahmi
No information about this author
et al.
Journal of Hydrology Regional Studies,
Journal Year:
2025,
Volume and Issue:
59, P. 102346 - 102346
Published: March 30, 2025
Language: Английский
Optimized intelligent learning for groundwater quality prediction in diverse aquifers of arid and semi-arid regions of India
Cleaner Engineering and Technology,
Journal Year:
2025,
Volume and Issue:
26, P. 100984 - 100984
Published: May 1, 2025
Language: Английский
Assessment of groundwater quality for agricultural purposes in Qazvin Province, northwestern Iran: A fuzzy inference and indicator Kriging approach
Environmental and Sustainability Indicators,
Journal Year:
2024,
Volume and Issue:
24, P. 100528 - 100528
Published: Nov. 6, 2024
Language: Английский