Evolving AI Algorithms
Evolving AI Algorithms
Embedded Files
eOGS: evolving Optimal Granular System
eOGS: evolving Optimal Granular System
- For classification:
Matlab code: [file 'eOGS Classification'] at the bottom of the page
- For prediction, function approximation, control:
Matlab code: [file 'eOGS Prediction'] at the bottom of the page
Relevant papers:
- Daniel Leite; Goran Andonovski; Igor Skrjanc; Fernando Gomide. "Optimal Rule-based Granular Systems from Data Streams." IEEE Transactions on Fuzzy Systems, 2019, DOI: 10.1109/TFUZZ.2019.2911493
- Daniel Leite; Igor Skrjanc. "Ensemble of evolving optimal granular experts, OWA aggregation, and time series prediction." Information Sciences, 504, pp. 95-112, 2019, DOI: 10.1016/j.ins.2019.07.053
eFGP: evolving Fuzzy Granular Predictor
eFGP: evolving Fuzzy Granular Predictor
Python code: [file 'eFGP Prediction'] at the bottom of the page
Relevant papers:
- Cristiano Garcia; Daniel Leite; Igor Skrjanc. "Incremental Missing-Data Imputation for Evolving Fuzzy Granular Prediction." IEEE Transactions on Fuzzy Systems, 2019, DOI: 10.1109/TFUZZ.2019.2935688
- Cristiano Garcia; Ahmed Esmin; Daniel Leite; Igor Skrjanc. "Evolvable fuzzy systems from data streams with missing values: With application to temporal pattern recognition and cryptocurrency prediction." Pattern Recognition Letters, 128, pp. 278-282, 2019, DOI: 10.1016/j.patrec.2019.09.012
FBeM: Fuzzy-set-Based evolving Modeling
FBeM: Fuzzy-set-Based evolving Modeling
Using trapezoidal membership functions:
- For classification:
Matlab code: [file 'FBeM Trapezoidal Classification - Rotating Gaussians'] at the bottom of the page
- For prediction, function approximation, control:
Matlab code: [file 'FBeM Trapezoidal - Death Valley'] at the bottom of the page
Python code: [file 'FBeM Trapezoidal Prediction - Python - Death Valley'] at the bottom of the page
Relevant papers:
- Daniel Leite; Rosangela Ballini; Pyramo Costa; Fernando Gomide. "Evolving fuzzy granular modeling from nonstationary fuzzy data streams." Evolving Systems - Springer, 3(2), pp. 65-79, 2012, DOI: 10.1007/s12530-012-9050-9
- Daniel Leite; Fernando Gomide. "Evolving linguistic fuzzy models from data streams." Book Chapter. In: Trillas E., Bonissone P., Magdalena L., Kacprzyk J. (eds) Combining Experimentation and Theory. Studies in Fuzziness and Soft Computing, 271, pp. 209-223, Springer, Berlin, Heidelberg, 2012, DOI: 10.1007/978-3-642-24666-1_15
- Lourenço Bueno; Pyramo Costa; Israel Mendes; Enderson Cruz; Daniel Leite. "Evolving ensemble of fuzzy models for multivariate time series prediction." In: IEEE International Conference on Fuzzy Systems, 2015, Istanbul - Turkey. FUZZ-IEEE'15. p. 6p. DOI: 10.1109/FUZZ-IEEE.2015.7338002
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Using Gaussian membership functions:
- For prediction, function approximation, control:
Matlab code: any of the following files [file 'FBeM Gauss - Gas Furnace BoxJenkins'] [file 'FBeM Gauss - Global40'] [file 'FBeM Gauss - MackeyGlass'] at the bottom of the page
Relevant papers:
- Eduardo Soares; Heloisa Camargo; Suzana Camargo; Daniel Leite. "Incremental Gaussian Granular Fuzzy Modeling Applied to Hurricane Track Forecasting." In: IEEE International Conference on Fuzzy Systems, 2018, Rio de Janeiro. FUZZ-IEEE'18, 2018. p. 8p. DOI: 10.1109/FUZZ-IEEE.2018.8491587
- Daniel Leite; Fernando Gomide; Rosangela Ballini; Pyramo Costa. "Fuzzy Granular Evolving Modeling for Time Series Prediction." In: IEEE International Conference on Fuzzy Systems, 2011, Taipei, Taiwan. FUZZ-IEEE'11, 2011. p. 2794-2801. DOI: 10.1109/FUZZY.2011.6007452
IBeM: Interval-Based evolving Modeling
IBeM: Interval-Based evolving Modeling
- For classification:
Matlab code: [file 'IBeM Classification - Rotating Gaussians'] at the bottom of the page
- For prediction, function approximation, control:
Matlab code: [file 'IBeM - Death Valley'] at the bottom of the page
Relevant papers:
- Daniel Leite; Pyramo Costa; Fernando Gomide. "Interval Approach for Evolving Granular System Modeling." Book Chapter. In: Sayed-Mouchaweh M., Lughofer E. (eds) Learning in Non-Stationary Environments, pp. 271-300, Springer, New York, NY, 2011. DOI: 10.1007/978-1-4419-8020-5_11
- Daniel Leite; Pyramo Costa; Fernando Gomide. "Granular Approach for Evolving Systems Modeling." Book Chapter. In: E. Hüllermeier, R. Kruse, and F. Hoffmann, Eds. Computational Intelligence for Knowledge-Based Systems Design, Lecture Notes in Computer Science, v. 6178, Springer, Verlag, Berlin, Heidelberg, p. 340-349, 2010. DOI: 10.1007/978-3-642-14049-5_35
eGNN: evolving Granular Neural Network
eGNN: evolving Granular Neural Network
- For classification:
Matlab code: [file 'eGNN Classification - Rotating Gaussians'] at the bottom of the page
Relevant papers (classification):
- Daniel Leite; Pyramo Costa; Fernando Gomide. "Evolving Granular Neural Network for Semi-Supervised Data Stream Classification." In: IEEE World Congress on Computational Intelligence, 2010, Barcelona, Spain. WCCI'10, 2010. p. 8p. DOI: 10.1109/IJCNN.2010.5596303
- Daniel Leite; Pyramo Costa; Fernando Gomide. "Evolving Granular Classification Neural Networks." In: IEEE International Joint Conference on Neural Networks, 2009, Atlanta, GA, US. IJCNN'09, 2009. p. 1736-1743. DOI: 10.1109/IJCNN.2009.5178895
- Daniel Leite. "Comparison of Genetic and Incremental Learning Methods for Neural Network-based Electrical Machine Fault Detection." Book Chapter. In: Lughofer E., Sayed-Mouchaweh M. (eds) Predictive Maintenance in Dynamic Systems. Springer, Cham, pp. 231-268, 2019. DOI: 10.1007/978-3-030-05645-2_8
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- For prediction, function approximation, control:
Matlab code: [file 'eGNN - Death Valley'] at the bottom of the page
Relevant papers (prediction):
- Daniel Leite; Pyramo Costa; Fernando Gomide. "Evolving granular neural networks from fuzzy data streams." Neural Networks, 38, pp. 1-16, 2013. DOI: 10.1016/j.neunet.2012.10.006
- Daniel Leite; Marcio Santana; Ana Borges; Fernando Gomide. "Fuzzy Granular Neural Network for incremental modeling of nonlinear chaotic systems." In: IEEE International Conference on Fuzzy Systems, 2016, Vancouver - Canada. FUZZ-IEEE'16, 2016. p. 64-71. DOI: 10.1109/FUZZ-IEEE.2016.7737669
- Daniel Leite; Pyramo Costa; Fernando Gomide. "Evolving granular neural network for fuzzy time series forecasting." In: International Joint Conference on Neural Networks, 2012, Brisbane - Australia. IJCNN'12, 2012. p. 8p. DOI: 10.1109/IJCNN.2012.6252382
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