Interpretability of linguistic fuzzy rule-based systems: An overview of interpretability measures
Linguistic fuzzy modelling, developed by linguistic fuzzy rule-based systems, allows us to
deal with the modelling of systems by building a linguistic model which could become …
deal with the modelling of systems by building a linguistic model which could become …
A historical review of evolutionary learning methods for Mamdani-type fuzzy rule-based systems: Designing interpretable genetic fuzzy systems
O Cordón - International journal of approximate reasoning, 2011 - Elsevier
The need for trading off interpretability and accuracy is intrinsic to the use of fuzzy systems.
The obtaining of accurate but also human-comprehensible fuzzy systems played a key role …
The obtaining of accurate but also human-comprehensible fuzzy systems played a key role …
Multiobjective evolutionary algorithms for electric power dispatch problem
MA Abido - IEEE transactions on evolutionary computation, 2006 - ieeexplore.ieee.org
The potential and effectiveness of the newly developed Pareto-based multiobjective
evolutionary algorithms (MOEA) for solving a real-world power system multiobjective …
evolutionary algorithms (MOEA) for solving a real-world power system multiobjective …
Genetic fuzzy systems: taxonomy, current research trends and prospects
F Herrera - Evolutionary Intelligence, 2008 - Springer
The use of genetic algorithms for designing fuzzy systems provides them with the learning
and adaptation capabilities and is called genetic fuzzy systems (GFSs). This topic has …
and adaptation capabilities and is called genetic fuzzy systems (GFSs). This topic has …
A review of the application of multiobjective evolutionary fuzzy systems: Current status and further directions
Over the past few decades, fuzzy systems have been widely used in several application
fields, thanks to their ability to model complex systems. The design of fuzzy systems has …
fields, thanks to their ability to model complex systems. The design of fuzzy systems has …
Heuristic design of fuzzy inference systems: A review of three decades of research
This paper provides an in-depth review of the optimal design of type-1 and type-2 fuzzy
inference systems (FIS) using five well known computational frameworks: genetic-fuzzy …
inference systems (FIS) using five well known computational frameworks: genetic-fuzzy …
Optimization of interval type-2 fuzzy logic controllers for a perturbed autonomous wheeled mobile robot using genetic algorithms
We describe a tracking controller for the dynamic model of a unicycle mobile robot by
integrating a kinematic and a torque controller based on type-2 fuzzy logic theory and …
integrating a kinematic and a torque controller based on type-2 fuzzy logic theory and …
Autonomous learning for fuzzy systems: a review
As one of the three pillars in computational intelligence, fuzzy systems are a powerful
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …
Low-level interpretability and high-level interpretability: a unified view of data-driven interpretable fuzzy system modelling
This paper aims at providing an in-depth overview of designing interpretable fuzzy inference
models from data within a unified framework. The objective of complex system modelling is …
models from data within a unified framework. The objective of complex system modelling is …
Network intrusion detection based on deep learning model optimized with rule-based hybrid feature selection
ABSTRACT Network Intrusion Detection System (NIDS) is often used to classify network
traffic in an attempt to protect computer systems from various network attacks. A major …
traffic in an attempt to protect computer systems from various network attacks. A major …