This thesis reports the work of using simulated annealing to design more efficient fuzzy logic systems to model problems with associated uncertainties. Simulated annealing is
used within this work as a method for learning the best configurations of type-1 and
type-2 fuzzy logic systems to maximise their modelling ability. Therefore, it presents
the combination of simulated annealing with three models, type-1 fuzzy logic systems,
interval type-2 fuzzy logic systems and general type-2 fuzzy logic systems to model
four bench-mark problems including real-world problems. These problems are: noise-free
Mackey-Glass time series forecasting, noisy Mackey-Glass time series forecasting
and two real world problems which are: the estimation of the low voltage electrical
line length in rural towns and the estimation of the medium voltage electrical line
maintenance cost. The type-1 and type-2 fuzzy logic systems models are compared in
their abilities to model uncertainties associated with these problems. Also, issues related
to this combination between simulated annealing and fuzzy logic systems including
type-2 fuzzy logic systems are discussed.
The thesis contributes to knowledge by presenting novel contributions. The first is
a novel approach to design interval type-2 fuzzy logic systems using the simulated
annealing algorithm. Another novelty is related to the first automatic design of general
type-2 fuzzy logic system using the vertical slice representation and a novel method
to overcome some parametrisation difficulties when learning general type-2 fuzzy logic
systems. The work shows that interval type-2 fuzzy logic systems added more abilities
to modelling information and handling uncertainties than type-1 fuzzy logic systems but
with a cost of more computations and time. For general type-2 fuzzy logic systems, the
clear conclusion that learning the third dimension can add more abilities to modelling
is an important advance in type-2 fuzzy logic systems research and should open the
doors for more promising research and practical works on using general type-2 fuzzy
logic systems to modelling applications despite the more computations associated with
it
