Accurate Prediction Using Triangular Type-2 Fuzzy Linear Regression: Simplifying Complex T2F Calculations

Author:

Zare Assef1,Shoeibi Afshin2,Bajestani Narges Shafaei3,Moridian Parisa4,Alizadehsani Roohallah5,Hallaji Majid6,Khosravi Abbas5

Affiliation:

1. Department of Electrical Engineering, Islamic Azad University, Gonabad, Khorasan Razavi, Iran

2. Faculty of Electrical Engineering, FGPA Lab, K. N. Toosi University of Technology, Tehran, Iran

3. Department of Electrical Engineering, Islamic Azad University, Gonabad Branch, Khorasan Razavi, Iran

4. Faculty of Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

5. Institute for Intelligent Systems Research and Innovation, Deakin University, Victoria, Australia

6. Electrical Engineering Faculty of the Islamic, Azad University, Neyshabure, Khorasan Razavi, Iran

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Human-Computer Interaction,Human Factors and Ergonomics,Control and Systems Engineering

Reference69 articles.

1. Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images

2. Automatic diagnosis of COVID-19 from CT images using CycleGAN and transfer learning;ghassemi,2021

3. Application of optimized Type 2 fuzzy time series to forecast Taiwan stock index

4. Possibilistic type-2 fuzzy regression with application to TAIEX forecasting;bajestani;Majlesi J of Mechatronic Sys,2016

5. A novel alpha-cut representation for type-2 fuzzy sets

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