Evolving fuzzy classifiers using different model architectures
Fuzzy Sets and Systems
Human-machine interaction issues in quality control based on online image classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Associating visual textures with human perceptions using genetic algorithms
Information Sciences: an International Journal
Fuzzy CMAC with incremental Bayesian Ying-Yang learning and dynamic rule construction
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
eFSM: a novel online neural-fuzzy semantic memory model
IEEE Transactions on Neural Networks
SparseFIS: data-driven learning of fuzzy systems with sparsity constraints
IEEE Transactions on Fuzzy Systems
Assessment of the influence of adaptive components in trainable surface inspection systems
Machine Vision and Applications - Integrated Imaging and Vision Techniques for Industrial Inspection
Variational bayes for a mixed stochastic/deterministic fuzzy filter
IEEE Transactions on Fuzzy Systems
Qualitative modeling of dynamical systems employing continuous-time recurrent fuzzy systems
Fuzzy Sets and Systems
On-line incremental feature weighting in evolving fuzzy classifiers
Fuzzy Sets and Systems
Handling drifts and shifts in on-line data streams with evolving fuzzy systems
Applied Soft Computing
A self-organizing fuzzy neural network based on a growing-and-pruning algorithm
IEEE Transactions on Fuzzy Systems
An affine fuzzy model with local and global interpretations
Applied Soft Computing
On-line valuation of residential premises with evolving fuzzy models
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
Investigation of evolving fuzzy systems methods FLEXFIS and eTS on predicting residential prices
WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
Modeling human aesthetic perception of visual textures
ACM Transactions on Applied Perception (TAP)
A new systematic design for Habitually Linear Evolving TS Fuzzy Model
Expert Systems with Applications: An International Journal
Thermal modeling of power transformers using evolving fuzzy systems
Engineering Applications of Artificial Intelligence
On employing fuzzy modeling algorithms for the valuation of residential premises
Information Sciences: an International Journal
Evolving fuzzy classifier based on the modified ECM algorithm for pattern classification
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Adaptive fault detection and diagnosis using an evolving fuzzy classifier
Information Sciences: an International Journal
Local model network identification for online engine modelling
Information Sciences: an International Journal
Online extraction of main linear trends for nonlinear time-varying processes
Information Sciences: an International Journal
Evolving fuzzy pattern trees for binary classification on data streams
Information Sciences: an International Journal
Optimal experiment design based on local model networks and multilayer perceptron networks
Engineering Applications of Artificial Intelligence
An attempt to employ genetic fuzzy systems to predict from a data stream of premises transactions
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
Evolving Takagi-Sugeno fuzzy model based on switching to neighboring models
Applied Soft Computing
A fast learning algorithm for evolving neo-fuzzy neuron
Applied Soft Computing
Evolving intelligent algorithms for the modelling of brain and eye signals
Applied Soft Computing
Water leakage forecasting: the application of a modified fuzzy evolving algorithm
Applied Soft Computing
A similarity-based approach for data stream classification
Expert Systems with Applications: An International Journal
kENFIS: kNN-based evolving neuro-fuzzy inference system for computer worms detection
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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In this paper, we introduce a new algorithm for incremental learning of a specific form of Takagi-Sugeno fuzzy systems proposed by Wang and Mendel in 1992. The new data-driven online learning approach includes not only the adaptation of linear parameters appearing in the rule consequents, but also the incremental learning of premise parameters appearing in the membership functions (fuzzy sets), together with a rule learning strategy in sample mode. A modified version of vector quantization is exploited for rule evolution and an incremental learning of the rules' premise parts. The modifications include an automatic generation of new clusters based on the nature, distribution, and quality of new data and an alternative strategy for selecting the winning cluster (rule) in each incremental learning step. Antecedent and consequent learning are connected in a stable manner, meaning that a convergence toward the optimal parameter set in the least-squares sense can be achieved. An evaluation and a comparison to conventional batch methods based on static and dynamic process models are presented for high-dimensional data recorded at engine test benches and at rolling mills. For the latter, the obtained data-driven fuzzy models are even compared with an analytical physical model. Furthermore, a comparison with other evolving fuzzy systems approaches is carried out based on nonlinear dynamic system identification tasks and a three-input nonlinear function approximation example.