What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
Fernando Gomide focuses on Fuzzy logic, Fuzzy control system, Neuro-fuzzy, Artificial intelligence and Fuzzy set operations.
His Fuzzy logic research incorporates elements of Computational intelligence, Data stream mining, Data mining and Time series.
His work is dedicated to discovering how Fuzzy control system, Fuzzy set are connected with Theoretical computer science and other disciplines.
His biological study spans a wide range of topics, including Control system, Fuzzy rule and Adaptive neuro fuzzy inference system.
His Artificial intelligence study combines topics in areas such as Machine learning and Petri net.
His study in Fuzzy set operations is interdisciplinary in nature, drawing from both Fuzzy number, Defuzzification and Fuzzy classification.
His most cited work include:
- An introduction to fuzzy sets : analysis and design (914 citations)
- Ten years of genetic fuzzy systems: current framework and new trends (750 citations)
- Fuzzy Systems Engineering: Toward Human-Centric Computing (470 citations)
What are the main themes of his work throughout his whole career to date?
Fuzzy logic, Artificial intelligence, Fuzzy control system, Fuzzy set and Neuro-fuzzy are his primary areas of study.
Fernando Gomide does research in Fuzzy logic, focusing on Fuzzy rule specifically.
As part of his studies on Artificial intelligence, he frequently links adjacent subjects like Machine learning.
His work deals with themes such as Intelligent decision support system, Theoretical computer science and Computational intelligence, which intersect with Fuzzy set.
His Neuro-fuzzy study integrates concerns from other disciplines, such as Fuzzy set operations, Deep learning and Adaptive neuro fuzzy inference system.
He has researched Fuzzy set operations in several fields, including Fuzzy number and Defuzzification.
He most often published in these fields:
- Fuzzy logic (47.00%)
- Artificial intelligence (45.00%)
- Fuzzy control system (27.67%)
What were the highlights of his more recent work (between 2012-2020)?
- Fuzzy logic (47.00%)
- Artificial intelligence (45.00%)
- Fuzzy control system (27.67%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Fuzzy logic, Artificial intelligence, Fuzzy control system, Fuzzy rule and Machine learning.
The various areas that Fernando Gomide examines in his Fuzzy logic study include Data stream mining, Data mining, Volatility, Econometrics and Cluster analysis.
As a part of the same scientific family, he mostly works in the field of Data mining, focusing on Fuzzy set operations and, on occasion, Fuzzy number.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Algorithm and Series.
A large part of his Fuzzy control system studies is devoted to Membership function.
The Machine learning study combines topics in areas such as Differential evolution, Genetic fuzzy systems and Search algorithm.
Between 2012 and 2020, his most popular works were:
- Adaptive fault detection and diagnosis using an evolving fuzzy classifier (118 citations)
- Evolving granular analytics for interval time series forecasting (84 citations)
- Evolving granular neural networks from fuzzy data streams (77 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
Fernando Gomide mostly deals with Fuzzy logic, Artificial neural network, Artificial intelligence, Neuro-fuzzy and Fuzzy rule.
He works in the field of Fuzzy logic, focusing on Fuzzy control system in particular.
He combines subjects such as Scheme, Membership function and Variable with his study of Artificial neural network.
Fernando Gomide interconnects Machine learning and Adaptive neuro fuzzy inference system in the investigation of issues within Neuro-fuzzy.
His Fuzzy rule study combines topics from a wide range of disciplines, such as Data modeling, Econometrics, Adaptive system and Stochastic volatility.
His work focuses on many connections between Data mining and other disciplines, such as Fuzzy set operations, that overlap with his field of interest in Fuzzy classification and Fuzzy number.
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