Machine learning algorithm for estimating and optimizing the phytochemical content and physicochemical properties of okra slices in an infrared heating system
Hany S. El‐Mesery,
Ahmed H. ElMesiry,
Evans K Quaye
и другие.
Food Chemistry X,
Год журнала:
2025,
Номер
unknown, С. 102248 - 102248
Опубликована: Янв. 1, 2025
Язык: Английский
Application of Experimental, Numerical, and Machine Learning Techniques to Improve Drying Performance and Decrease Energy Consumption Infrared Continuous Dryer
Case Studies in Thermal Engineering,
Год журнала:
2025,
Номер
unknown, С. 106025 - 106025
Опубликована: Март 1, 2025
Язык: Английский
Drying Time, Energy and Exergy Efficiency Prediction of Corn (Zea mays L.) at a Convective-Infrared-Rotary Dryer: Approach by an Artificial Neural Network
Energies,
Год журнала:
2025,
Номер
18(3), С. 696 - 696
Опубликована: Фев. 3, 2025
Energy
consumption
in
the
drying
industry
has
made
an
energy-intensive
operation.
In
this
study,
time,
quality
properties
(color,
shrinkage,
water
activity
and
rehydration
ratio),
specific
energy
(S.E.C),
thermal,
exergy
efficiency
of
corn
using
a
hybrid
dryer
convective-infrared-rotary
(CV-IR-D)
were
analyzed.
addition,
parameters
predicted
artificial
neural
network
(ANN)
technique.
The
experiments
conducted
at
three
rotary
rotation
speeds
4,
8
12
rpm,
temperatures
45,
55
65
°C,
infrared
power
0.25,
0.5
0.75
kW.
By
increasing
temperature,
speed,
S.E.C
decreased
while
Deff,
energy,
thermal
increased.
highest
values
ratio
redness
(a*)
lowest
brightness
(L*),
yellowness
(b*)
color
changes
(ΔE)
obtained
kW,
air
temperature
°C
speed
rpm.
range
S.E.C,
during
process
was
5.05–28.15
MJ/kg,
3.26–29.29%,
5.5–32.33%
21.22–55.35%.
prediction
results
ANNs
showed
that
R
for
data
0.9938,
0.9906,
0.9965,
0.9874
0.9893,
respectively,
indicating
successful
prediction.
Язык: Английский
Computational intelligence and machine learning Approaches for performance evaluation of an infrared dryer: Quality analysis, drying kinetics, and thermal performance
Journal of Stored Products Research,
Год журнала:
2025,
Номер
112, С. 102639 - 102639
Опубликована: Март 25, 2025
Язык: Английский
Evaluating and predicting the impact of storage conditions and packaging materials on the physical properties of paddy rice using machine learning approaches and artificial neural networks
Journal of Stored Products Research,
Год журнала:
2025,
Номер
112, С. 102659 - 102659
Опубликована: Апрель 19, 2025
Язык: Английский