Juan R. Castro

About Juan R. Castro

Juan R. Castro, With an exceptional h-index of 29 and a recent h-index of 23 (since 2020), a distinguished researcher at Universidad Autónoma de Baja California, specializes in the field of Computational Intelligence, Type-2 Fuzzy Systems, Fuzzy Neural Networks, Fuzzy Deep Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

A type-3 fuzzy parameter adjustment in harmony search for the parameterization of fuzzy controllers

A new approach for interval type-3 fuzzy control of nonlinear plants

Interval type-3 fuzzy differential evolution for parameterization of fuzzy controllers

A Methodology for Building of Interval and General Type-2 Fuzzy Systems Based on the Principle of Justifiable Granularity.

Forecasting the COVID-19 with interval type-3 fuzzy logic and the fractal dimension

Interval type-3 fuzzy systems: a natural evolution from type-1 and type-2 fuzzy systems

Interval type-3 fuzzy aggregation of neural networks for multiple time series prediction: the case of financial forecasting

Type-2 fuzzy logic systems

Juan R. Castro Information

University

Position

___

Citations(all)

4853

Citations(since 2020)

2764

Cited By

3555

hIndex(all)

29

hIndex(since 2020)

23

i10Index(all)

81

i10Index(since 2020)

51

Email

University Profile Page

Google Scholar

Juan R. Castro Skills & Research Interests

Computational Intelligence

Type-2 Fuzzy Systems

Fuzzy Neural Networks

Fuzzy Deep Learning

Top articles of Juan R. Castro

A type-3 fuzzy parameter adjustment in harmony search for the parameterization of fuzzy controllers

International Journal of Fuzzy Systems

2023/9

A new approach for interval type-3 fuzzy control of nonlinear plants

International Journal of Fuzzy Systems

2023/6

Interval type-3 fuzzy differential evolution for parameterization of fuzzy controllers

International Journal of Fuzzy Systems

2023/6

A Methodology for Building of Interval and General Type-2 Fuzzy Systems Based on the Principle of Justifiable Granularity.

Journal of Multiple-Valued Logic & Soft Computing

2023/5/1

Forecasting the COVID-19 with interval type-3 fuzzy logic and the fractal dimension

International Journal of Fuzzy Systems

2023/2

Interval type-3 fuzzy systems: a natural evolution from type-1 and type-2 fuzzy systems

2023/1/28

Interval type-3 fuzzy aggregation of neural networks for multiple time series prediction: the case of financial forecasting

Axioms

2022/5/26

Type-2 fuzzy logic systems

2022/3/14

Interval type-3 fuzzy sets

2022/3/14

Introduction to interval type-3 fuzzy systems

2022/3/14

Interval type-3 fuzzy logic systems (IT3FLS)

2022/3/14

Conclusions of Type-3 Fuzzy Systems

2022/3/14

Interval type-3 fuzzy systems: theory and design

2022/3/13

Interpretable Mamdani neuro-fuzzy model through context awareness and linguistic adaptation

Expert Systems with Applications

2022/3/1

Interval type-3 fuzzy fractal approach in sound speaker quality control evaluation

Engineering Applications of Artificial Intelligence

2022/11/1

A methodology for building interval type‐3 fuzzy systems based on the principle of justifiable granularity

International Journal of Intelligent Systems

2022/10

Interval type-3 fuzzy adaptation of the bee colony optimization algorithm for optimal fuzzy control of an autonomous mobile robot

Micromachines

2022/9/7

Interval type-3 fuzzy aggregators for ensembles of neural networks in COVID-19 time series prediction

Engineering Applications of Artificial Intelligence

2022/9/1

Design of type-3 fuzzy systems and ensemble neural networks for COVID-19 time series prediction using a firefly algorithm

Axioms

2022/8/17

Knowledge transfer for labeling unknown fuzzy sets using Grammar-Guided Genetic Algorithms

Applied Soft Computing

2022/7/1

See List of Professors in Juan R. Castro University(Universidad Autónoma de Baja California)

Co-Authors

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