An approach for non-singleton generalized Type-2 fuzzy classifiers

[1]  Christian Wagner,et al.  Contrasting singleton type-1 and interval type-2 non-singleton type-1 fuzzy logic systems , 2016, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[2]  Héctor Pomares,et al.  On comparing non-singleton type-1 and singleton type-2 fuzzy controllers for a nonlinear servo system , 2011, 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ).

[3]  Piero P. Bonissone,et al.  A fuzzy random forest , 2010, Int. J. Approx. Reason..

[4]  Min Zhou,et al.  Footprint of uncertainty for type-2 fuzzy sets , 2014, Inf. Sci..

[5]  Feilong Liu,et al.  An efficient centroid type-reduction strategy for general type-2 fuzzy logic system , 2008, Inf. Sci..

[6]  Patricia Melin,et al.  Toward a development of general type-2 fuzzy classifiers applied in diagnosis problems through embedded type-1 fuzzy classifiers , 2020, Soft Comput..

[7]  Mehrbakhsh Nilashi,et al.  Fuzzy logic approach for infectious disease diagnosis: A methodical evaluation, literature and classification , 2019, Biocybernetics and Biomedical Engineering.

[8]  Shitong Wang,et al.  Bayesian Takagi–Sugeno–Kang Fuzzy Classifier , 2017, IEEE Transactions on Fuzzy Systems.

[9]  Saeid Nahavandi,et al.  Developing a computationally effective Interval Type-2 TSK Fuzzy Logic Controller , 2020, J. Intell. Fuzzy Syst..

[10]  Sunny Thukral,et al.  Versatility of fuzzy logic in chronic diseases: A review. , 2019, Medical hypotheses.

[11]  Oscar Castillo,et al.  High order α-planes integration: A new approach to computational cost reduction of General Type-2 Fuzzy Systems , 2018, Eng. Appl. Artif. Intell..

[12]  Joo-Ho Lee,et al.  Heartbeat classification using local transform pattern feature and hybrid neural fuzzy-logic system based on self-organizing map , 2020, Biomed. Signal Process. Control..

[14]  Jerry M. Mendel,et al.  Interval type-2 fuzzy logic systems , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).

[15]  Hani Hagras,et al.  Towards comparing adaptive type-2 input based non-singleton type-2 FLS and non-singleton FLSs employing Gaussian inputs , 2012, 2012 IEEE International Conference on Fuzzy Systems.

[16]  Martin Tabakov,et al.  A new reasoning approach combining information systems and interval type-2 fuzzy sets , 2019, J. Intell. Fuzzy Syst..

[17]  P. M. Pradhan,et al.  Design of interval type-2 fuzzy precompensated PID controller applied to two-DOF robotic manipulator with variable payload. , 2019, ISA transactions.

[18]  Teck Wee Chua,et al.  Non-singleton genetic fuzzy logic system for arrhythmias classification , 2011, Eng. Appl. Artif. Intell..

[19]  Zhen Zhao,et al.  Interval type-2 fuzzy tracking control for nonlinear systems via sampled-data controller , 2019, Fuzzy Sets Syst..

[20]  Simon Coupland Type-2 Fuzzy Sets: Geometric Defuzzification and Type-Reduction , 2007, 2007 IEEE Symposium on Foundations of Computational Intelligence.

[21]  Jing Wang Examination on face recognition method based on type 2 blurry , 2020, J. Intell. Fuzzy Syst..

[22]  Oscar Castillo,et al.  A review on the applications of type-2 fuzzy logic in classification and pattern recognition , 2013, Expert Syst. Appl..

[23]  Juan R. Castro,et al.  A comparative study of type-1 fuzzy logic systems, interval type-2 fuzzy logic systems and generalized type-2 fuzzy logic systems in control problems , 2016, Inf. Sci..

[24]  Changyin Wei,et al.  Numerical Investigation on Fuzzy Logic Control Energy Management Strategy of Parallel Hybrid Electric Vehicle , 2019, Energy Procedia.

[25]  Mohammad Hossein Fazel Zarandi,et al.  Multi-central general type-2 fuzzy clustering approach for pattern recognitions , 2016, Inf. Sci..

[26]  Oscar Castillo,et al.  Designing hybrid classifiers based on general type-2 fuzzy logic and support vector machines , 2020, Soft Comput..

[27]  Dongrui Wu,et al.  Computationally Efficient Type-Reduction Strategies for a Type-2 Fuzzy Logic Controller , 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..

[28]  Giuseppe De Pietro,et al.  Likelihood-fuzzy analysis: From data, through statistics, to interpretable fuzzy classifiers , 2018, Int. J. Approx. Reason..

[29]  Antero Arkkio,et al.  Detection of stator winding fault in induction motor using fuzzy logic , 2008, Appl. Soft Comput..

[30]  Sharaf AlKheder,et al.  Enhancing pedestrian safety, walkability and traffic flow with fuzzy logic. , 2019, The Science of the total environment.

[31]  Witold Pedrycz,et al.  Fuzzy granular classification based on the principle of justifiable granularity , 2019, Knowl. Based Syst..

[32]  Tahar Bahi,et al.  Condition Monitoring and Fault Detection in Wind Turbine Based on DFIG by the Fuzzy Logic , 2015 .

[33]  Jerry M. Mendel,et al.  Interval Type-2 Fuzzy Logic Systems Made Simple , 2006, IEEE Transactions on Fuzzy Systems.

[34]  Witold Pedrycz,et al.  Design of Reinforced Interval Type-2 Fuzzy C-Means-Based Fuzzy Classifier , 2018, IEEE Transactions on Fuzzy Systems.

[35]  Jianbin Qiu,et al.  Fuzzy Adaptive Finite-Time Fault-Tolerant Control for Strict-Feedback Nonlinear Systems , 2020, IEEE Transactions on Fuzzy Systems.

[36]  Jerry M. Mendel,et al.  $\alpha$-Plane Representation for Type-2 Fuzzy Sets: Theory and Applications , 2009, IEEE Transactions on Fuzzy Systems.

[37]  K. V. Arya,et al.  Traffic Management using Logistic Regression with Fuzzy Logic , 2018 .

[38]  Yan-Lin He,et al.  Energy modeling and saving potential analysis using a novel extreme learning fuzzy logic network: A case study of ethylene industry , 2018 .

[39]  Guang-Zhong Yang,et al.  A Self-Adaptive Online Brain–Machine Interface of a Humanoid Robot Through a General Type-2 Fuzzy Inference System , 2018, IEEE Transactions on Fuzzy Systems.

[40]  Yue Chen,et al.  Application of machine learning and image target recognition in English learning task , 2020, J. Intell. Fuzzy Syst..

[41]  Jerry M. Mendel,et al.  General Type-2 Fuzzy Logic Systems Made Simple: A Tutorial , 2014, IEEE Transactions on Fuzzy Systems.

[42]  Woei Wan Tan,et al.  Towards an efficient type-reduction method for interval type-2 fuzzy logic systems , 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

[43]  Patricia Melin,et al.  A hybrid design of shadowed type-2 fuzzy inference systems applied in diagnosis problems , 2019, Eng. Appl. Artif. Intell..

[44]  Jiaxin Liu,et al.  Similarity-based non-singleton general type-2 fuzzy logic controller with applications to mobile two-wheeled robots , 2019, J. Intell. Fuzzy Syst..

[45]  Oscar Castillo,et al.  New Methodology to Approximate Type-Reduction Based on a Continuous Root-Finding Karnik Mendel Algorithm , 2017, Algorithms.

[46]  Patricia Melin,et al.  Comparative study of interval Type-2 and general Type-2 fuzzy systems in medical diagnosis , 2020, Inf. Sci..

[47]  Oscar Castillo,et al.  Designing a general type-2 fuzzy expert system for diagnosis of depression , 2019, Appl. Soft Comput..

[48]  Hani Hagras,et al.  Toward General Type-2 Fuzzy Logic Systems Based on zSlices , 2010, IEEE Transactions on Fuzzy Systems.