Forecasting by general type-2 fuzzy logic systems optimized with QPSO algorithms
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[1] Oscar Castillo,et al. A review on the design and optimization of interval type-2 fuzzy controllers , 2012, Appl. Soft Comput..
[2] Jerry M. Mendel,et al. Enhanced Karnik--Mendel Algorithms , 2009, IEEE Transactions on Fuzzy Systems.
[3] Patricia Melin,et al. Particle swarm optimization of interval type-2 fuzzy systems for FPGA applications , 2013, Appl. Soft Comput..
[4] Yu-Lin He,et al. Particle swarm optimization for determining fuzzy measures from data , 2011, Inf. Sci..
[5] Dongrui Wu,et al. On the Fundamental Differences Between Interval Type-2 and Type-1 Fuzzy Logic Controllers , 2012, IEEE Transactions on Fuzzy Systems.
[6] Andreas S. Weigend,et al. Time Series Prediction: Forecasting the Future and Understanding the Past , 1994 .
[7] Jeng-Shyang Pan,et al. Fuzzy Rules Interpolation for Sparse Fuzzy Rule-Based Systems Based on Interval Type-2 Gaussian Fuzzy Sets and Genetic Algorithms , 2013, IEEE Transactions on Fuzzy Systems.
[8] Jinde Cao,et al. Dynamical behaviors of discrete-time fuzzy cellular neural networks with variable delays and impulses , 2008, J. Frankl. Inst..
[9] Xiaojun Wu,et al. Convergence analysis and improvements of quantum-behaved particle swarm optimization , 2012, Inf. Sci..
[10] Gerardo M. Mendez,et al. Hybrid learning for interval type-2 fuzzy logic systems based on orthogonal least-squares and back-propagation methods , 2009, Inf. Sci..
[11] Oscar Castillo,et al. An improved sobel edge detection method based on generalized type-2 fuzzy logic , 2014, Soft Computing.
[12] Hani Hagras,et al. Towards the Wide Spread Use of Type-2 Fuzzy Logic Systems in Real World Applications , 2012, IEEE Computational Intelligence Magazine.
[13] Jerry M. Mendel,et al. On KM Algorithms for Solving Type-2 Fuzzy Set Problems , 2013, IEEE Transactions on Fuzzy Systems.
[14] 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..
[15] Oscar Castillo,et al. An optimization method for designing type-2 fuzzy inference systems based on the footprint of uncertainty using genetic algorithms , 2012, Expert Syst. Appl..
[16] Jerry M. Mendel,et al. UNIVERSAL IMAGE NOISE REMOVAL FILTER BASED ON TYPE-2 FUZZY LOGIC SYSTEM AND QPSO , 2012 .
[17] Oscar Castillo,et al. Generalized Type-2 Fuzzy Systems for controlling a mobile robot and a performance comparison with Interval Type-2 and Type-1 Fuzzy Systems , 2015, Expert Syst. Appl..
[18] Jerry M. Mendel,et al. General Type-2 Fuzzy Logic Systems Made Simple: A Tutorial , 2014, IEEE Transactions on Fuzzy Systems.
[19] Chia-Feng Juang,et al. Evolutionary Robot Wall-Following Control Using Type-2 Fuzzy Controller With Species-DE-Activated Continuous ACO , 2013, IEEE Transactions on Fuzzy Systems.
[20] Karim Djouani,et al. A robust interval Type-2 TSK Fuzzy Logic System design based on Chebyshev fitting , 2012 .
[21] P. Latha,et al. An Effective Torque Ripple Reduction for Permanent Magnet Synchronous Motor Using Ant Colony Optimization , 2015, Int. J. Fuzzy Syst..
[22] Chia-Feng Juang,et al. Designing Fuzzy-Rule-Based Systems Using Continuous Ant-Colony Optimization , 2010, IEEE Transactions on Fuzzy Systems.
[23] D. Srinivasan,et al. Interval Type-2 Fuzzy Logic Systems for Load Forecasting: A Comparative Study , 2012, IEEE Transactions on Power Systems.
[24] Mohammad Hossein Fazel Zarandi,et al. A type-2 fuzzy rule-based expert system model for stock price analysis , 2009, Expert Syst. Appl..
[25] Oscar Castillo,et al. Optimization of type-2 fuzzy weights in backpropagation learning for neural networks using GAs and PSO , 2016, Appl. Soft Comput..
[26] Dazhi Wang,et al. Forecasting studies by designing Mamdani interval type-2 fuzzy logic systems: With the combination of BP algorithms and KM algorithms , 2016, Neurocomputing.
[27] Saeid Nahavandi,et al. Load Forecasting Using Interval Type-2 Fuzzy Logic Systems: Optimal Type Reduction , 2014, IEEE Transactions on Industrial Informatics.
[28] Claudia I. González,et al. Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic , 2017 .
[29] Hani Hagras,et al. Toward General Type-2 Fuzzy Logic Systems Based on zSlices , 2010, IEEE Transactions on Fuzzy Systems.
[30] Oscar Castillo,et al. Edge-Detection Method for Image Processing Based on Generalized Type-2 Fuzzy Logic , 2014, IEEE Transactions on Fuzzy Systems.
[31] Jerry M. Mendel,et al. $\alpha$-Plane Representation for Type-2 Fuzzy Sets: Theory and Applications , 2009, IEEE Transactions on Fuzzy Systems.
[32] Ioannis B. Theocharis,et al. Locally recurrent neural networks for wind speed prediction using spatial correlation , 2007, Inf. Sci..
[33] Jerry M. Mendel,et al. Study on enhanced Karnik-Mendel algorithms: Initialization explanations and computation improvements , 2012, Inf. Sci..
[34] George J. Klir,et al. Fuzzy sets and fuzzy logic - theory and applications , 1995 .
[35] J. Mendel. Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions , 2001 .
[36] Vincent DeGeorge,et al. Amorphous and Nanocomposite Materials for Energy-Efficient Electric Motors , 2015, Journal of Electronic Materials.
[37] Saeid Nahavandi,et al. Effects of type reduction algorithms on forecasting accuracy of IT2FLS models , 2014, Appl. Soft Comput..
[38] Fuad E. Alsaadi,et al. Adaptive fuzzy prescribed performance controller design for a class of uncertain fractional-order nonlinear systems with external disturbances , 2017, Neurocomputing.
[39] Feilong Liu,et al. An efficient centroid type-reduction strategy for general type-2 fuzzy logic system , 2008, Inf. Sci..