The following publications are possibly variants of this publication:
- Interval type-2 non-singleton type-2 Takagi-Sugeno-Kang fuzzy logic systems using the hybrid learning mechanism recursive-least-square and back-propagation methodsGerardo M. Mendez, María de los Angeles Hernandez M.. icarcv 2010: 710-714 [doi]
- Interval Type-1 Non-Singleton Type-2 TSK Fuzzy Logic Systems Using the Hybrid Training Method RLS-BPGerardo M. Mendez, M.-A. Hernandez. foci 2007: 370-374 [doi]
- Interval Type-1 Non-singleton Type-2 TSK Fuzzy Logic Systems Using the Hybrid Training Method RLS-BPGerardo M. Mendez. In Patricia Melin, Oscar Castillo, Eduardo Gómez-Ramírez, Janusz Kacprzyk, Witold Pedrycz, editors, Analysis and Design of Intelligent Systems using Soft Computing Techniques, a selection of papers from IFSA 2007. Volume 41 of Advances in Soft Computing, pages 36-44, Springer, 2007. [doi]
- A hybrid learning method composed by the orthogonal least-squares and the back-propagation learning algorithms for interval A2-C1 type-1 non-singleton type-2 TSK fuzzy logic systemsMaría de los Angeles Hernandez M., Patricia Melin, Gerardo M. Mendez, Oscar Castillo, Ismael López-Juarez. soco, 19(3):661-678, 2015. [doi]
- Hybrid learning for interval type-2 fuzzy logic systems based on orthogonal least-squares and back-propagation methodsGerardo M. Mendez, MarÃa de los Angeles Hernandez M.. isci, 179(13):2146-2157, 2009. [doi]
- Orthogonal-least-squares and backpropa- gation hybrid learning algorithm for interval A2-C1 singleton type-2 Takagi-Sugeno-Kang fuzzy logic systemsGerardo M. Mendez, J. Cruz Martinez, David S. González, F. Javier Rendón-Espinoza. ijhis, 11(2):125-135, 2014. [doi]
- First-Order Interval Type-1 Non-singleton Type-2 TSK Fuzzy Logic SystemsGerardo M. Mendez, Luis Adolfo Leduc. micai 2006: 81-89 [doi]
- First-order interval type-1 non-singleton type-2 TSK fuzzy logic systemsGerardo M. Mendez, Luis Adolfo Leduc, María de los Angeles Hernandez M.. iastedCI 2006: 269-273
- Interval Type-2 TSK Fuzzy Logic Systems Using Hybrid Learning AlgorithmGerardo M. Mendez, Oscar Castillo. fuzzIEEE 2005: 230-235 [doi]
- Hybrid Interval Type-1 Non-singleton Type-2 Fuzzy Logic Systems Are Type-2 Adaptive Neuro-fuzzy Inference SystemsGerardo M. Mendez, María de los Angeles Hernandez Medina. In Oscar Castillo, Witold Pedrycz, Janusz Kacprzyk, editors, Evolutionary Design of Intelligent Systems in Modeling, Simulation and Control. Volume 257 of Studies in Computational Intelligence, pages 53-61, Springer, 2009. [doi]
- Hybrid learning mechanism for interval A2-C1 type-2 non-singleton type-2 Takagi-Sugeno-Kang fuzzy logic systemsGerardo M. Mendez, María de los Angeles Hernandez M.. isci, 220:149-169, 2013. [doi]
- Type-1 Non-singleton Type-2 Takagi-Sugeno-Kang Fuzzy Logic Systems Using the Hybrid Mechanism Composed by a Kalman Type Filter and Back Propagation MethodsGerardo M. Mendez, María de los Angeles Hernandez M., Alberto Cavazos, Marco-Tulio Mata-Jiménez. HAIS 2010: 429-437 [doi]
- Modelling and Prediction of the MXNUSD Exchange Rate Using Interval Singleton Type-2 Fuzzy Logic SystemsMarÃa de los Angeles Hernandez Medina, Gerardo M. Mendez. engl, 15(1):69-72, 2007. [doi]