Energies,
Journal Year:
2024,
Volume and Issue:
18(1), P. 16 - 16
Published: Dec. 24, 2024
The
increasing
demand
for
sustainable
energy
has
spurred
interest
in
biofuels
as
a
renewable
alternative
to
fossil
fuels.
Biomass
gasification
and
pyrolysis
are
two
prominent
thermochemical
conversion
processes
biofuel
production.
While
these
effective,
they
often
influenced
by
complex,
nonlinear,
uncertain
factors,
making
optimization
prediction
challenging.
This
study
highlights
the
application
of
fuzzy
neural
networks
(FNNs)—a
hybrid
approach
that
integrates
strengths
logic
networks—as
novel
tool
address
challenges.
Unlike
traditional
methods,
FNNs
offer
enhanced
adaptability
accuracy
modeling
nonlinear
systems,
them
uniquely
suited
biomass
processes.
review
not
only
ability
optimize
predict
performance
but
also
identifies
their
role
advancing
decision-making
frameworks.
Key
challenges,
benefits,
future
research
opportunities
explored,
showcasing
transformative
potential
Governments
around
the
world
have
been
developing
political
and
economic
tools
to
tackle
serious
environmental
issues
caused
by
indiscriminate
exploitation
of
fossil
fuels.
Moreover,
United
Nations'
17
Sustainable
Development
Goals
(SDGs)
refreshed
world's
approach
tackling
sustainability
highlighted
need
for
coordinated
action
from
a
variety
societal
players.
The
bioeconomy
circular
economy
are
popular
narratives
that
included
in
idea
sustainability.
Therefore,
reduce
stress
enhance
security
supply
primary
raw
materials,
transition
linear
is
essential.
or
requires
adopting
sustainable
agriculture
systems
where
concept
"cradle
grave"
implemented.
Current
management
practices
vast
amounts
agro-industrial
waste
generated
globally
such
as
landfill
incineration
not
considered
environmentally
friendly
strategies.
cultivation
different
food
crops
could
experience
decrease
production
GHG
emissions
if
residual
biomass
valued
put
back
into
system
using
"closing
loop"
strategy.
This
strategy
would
also
support
growth
achievement
SDGs.
Energies,
Journal Year:
2024,
Volume and Issue:
18(1), P. 16 - 16
Published: Dec. 24, 2024
The
increasing
demand
for
sustainable
energy
has
spurred
interest
in
biofuels
as
a
renewable
alternative
to
fossil
fuels.
Biomass
gasification
and
pyrolysis
are
two
prominent
thermochemical
conversion
processes
biofuel
production.
While
these
effective,
they
often
influenced
by
complex,
nonlinear,
uncertain
factors,
making
optimization
prediction
challenging.
This
study
highlights
the
application
of
fuzzy
neural
networks
(FNNs)—a
hybrid
approach
that
integrates
strengths
logic
networks—as
novel
tool
address
challenges.
Unlike
traditional
methods,
FNNs
offer
enhanced
adaptability
accuracy
modeling
nonlinear
systems,
them
uniquely
suited
biomass
processes.
review
not
only
ability
optimize
predict
performance
but
also
identifies
their
role
advancing
decision-making
frameworks.
Key
challenges,
benefits,
future
research
opportunities
explored,
showcasing
transformative
potential
