Fuzzy neural networks and neurocomputations
Fuzzy Sets and Systems
Interfaces of fuzzy models: a study in fuzzy information processing
Information Sciences: an International Journal
Fuzzy Sets and Systems
Uninorms in fuzzy systems modeling
Fuzzy Sets and Systems
Discretization: An Enabling Technique
Data Mining and Knowledge Discovery
Continuous generated associative aggregation operators
Fuzzy Sets and Systems
A Modified Chi2 Algorithm for Discretization
IEEE Transactions on Knowledge and Data Engineering
Hierarchical neuro-fuzzy quadtree models
Fuzzy Sets and Systems - Fuzzy models
On Changing Continuous Attributes into Ordered Discrete Attributes
EWSL '91 Proceedings of the European Working Session on Machine Learning
Fuzzy Data Mining: Effect of Fuzzy Discretization
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
An Evolutionary Algorithm Using Multivariate Discretization for Decision Rule Induction
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
On the reversibility of uninorms and t-operators
Fuzzy Sets and Systems - Mathematics
A hierarchical knowledge-based environment for linguistic modeling: models and iterative methodology
Fuzzy Sets and Systems - Theme: Learning and modeling
IEEE Transactions on Knowledge and Data Engineering
Cascade Architectures of Fuzzy Neural Networks
Fuzzy Optimization and Decision Making
Hybrid learning models to get the interpretability–accuracy trade-off in fuzzy modeling
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Reducing the number of parameters of a fuzzy system using scaling functions
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Uninorm-Based Logic Neurons as Adaptive and Interpretable Processing Constructs
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Fuzzy logic-based networks: A study in logic data interpretation: Research Articles
International Journal of Intelligent Systems
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
Fuzzy Sets and Systems
Fuzzy modelling through logic optimization
International Journal of Approximate Reasoning
Eliciting transparent fuzzy model using differential evolution
Applied Soft Computing
A methodology for automated fuzzy model generation
Fuzzy Sets and Systems
Interpretability constraints for fuzzy information granulation
Information Sciences: an International Journal
Differential evolution and particle swarm optimisation in partitional clustering
Computational Statistics & Data Analysis
TaSe, a Taylor series-based fuzzy system model that combines interpretability and accuracy
Fuzzy Sets and Systems
Analysis and design of hierarchical fuzzy systems
IEEE Transactions on Fuzzy Systems
On multistage fuzzy neural network modeling
IEEE Transactions on Fuzzy Systems
Fuzzy modeling of high-dimensional systems: complexity reduction and interpretability improvement
IEEE Transactions on Fuzzy Systems
Logic-Based Fuzzy Neurocomputing With Unineurons
IEEE Transactions on Fuzzy Systems
A neuro-fuzzy network to generate human-understandable knowledge from data
Cognitive Systems Research
Heterogeneous fuzzy logic networks: fundamentals and development studies
IEEE Transactions on Neural Networks
OR/AND neurons and the development of interpretable logic models
IEEE Transactions on Neural Networks
Fuzzy transforms of monotone functions with application to image compression
Information Sciences: an International Journal
Permutation-based finite implicative fuzzy associative memories
Information Sciences: an International Journal
A genetic reduction of feature space in the design of fuzzy models
Applied Soft Computing
Granular fuzzy models: a study in knowledge management in fuzzy modeling
International Journal of Approximate Reasoning
Triangular norm based graded convex fuzzy sets
Fuzzy Sets and Systems
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The ultimate challenges of system modeling concern designing accurate yet highly transparent and user-centric models. We have witnessed a plethora of neurofuzzy architectures which are aimed at addressing these two highly conflicting requirements. This study is concerned with the design and the development of transparent logic networks realized with the aid of fuzzy neurons and fuzzy unineurons. The construction of networks of this form requires a formation of efficient interfaces that constitute a conceptually appealing bridge between the model and the real-world experimental environment in which the model is to be used. In general, the interfaces are constructed by invoking some form of granulation of information; and binary (Boolean) discretization, in particular. We introduce a new discretization environment that is realized by means of particle swarm optimization (PSO) and data clustering implemented by the K-Means algorithm. The underlying structure of the network is optimized by invoking a combination of the PSO and the mechanisms of conventional gradient-based learning. We discuss various optimization strategies by considering Boolean as well as fuzzy data coming as the result of discretization of original experimental data and then involving several learning strategies. We elaborate on the interpretation aspects of the network and show how those could be strengthened through efficient pruning. We also show how the interpreted network leads to a simpler and more accurate logic description of the experimental data. A number of experimental studies are included.