What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Real number
Humberto Bustince focuses on Fuzzy rule, Fuzzy logic, Artificial intelligence, Machine learning and Discrete mathematics.
His Fuzzy rule study integrates concerns from other disciplines, such as Function, Fuzzy reasoning, Choquet integral and Monotonic function.
Humberto Bustince has researched Fuzzy logic in several fields, including Entropy and Unit interval.
His research brings together the fields of Data mining and Artificial intelligence.
His Discrete mathematics research integrates issues from Tuple, Associative property, Pure mathematics, Interval valued and Homogeneity.
Humberto Bustince interconnects Fuzzy number, Defuzzification and Fuzzy set operations in the investigation of issues within Fuzzy classification.
His most cited work include:
- A genetic tuning to improve the performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of ignorance and lateral position (110 citations)
- A Compact Evolutionary Interval-Valued Fuzzy Rule-Based Classification System for the Modeling and Prediction of Real-World Financial Applications With Imbalanced Data (102 citations)
- Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning (100 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Fuzzy logic, Fuzzy set, Discrete mathematics and Fuzzy rule.
Humberto Bustince has included themes like Machine learning, Data mining and Pattern recognition in his Artificial intelligence study.
His Fuzzy logic research includes elements of Context, Theoretical computer science, Negation, Measure and Thresholding.
Humberto Bustince has included themes like Algorithm and Algebra in his Fuzzy set study.
His work in Fuzzy rule addresses subjects such as Choquet integral, which are connected to disciplines such as Function.
His research investigates the link between Fuzzy set operations and topics such as Fuzzy classification that cross with problems in Defuzzification and Neuro-fuzzy.
He most often published in these fields:
- Artificial intelligence (35.38%)
- Fuzzy logic (26.46%)
- Fuzzy set (26.15%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (35.38%)
- Fuzzy logic (26.46%)
- Choquet integral (12.00%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Fuzzy logic, Choquet integral, Fuzzy set and Function.
His work carried out in the field of Artificial intelligence brings together such families of science as Extension, Data mining and Pattern recognition.
His Fuzzy logic research includes themes of Characterization, Context, Machine learning and Thresholding.
His Choquet integral study combines topics from a wide range of disciplines, such as Christian ministry, Enhanced Data Rates for GSM Evolution and Fuzzy rule.
His work deals with themes such as Classifier, Algorithm and Degree, which intersect with Fuzzy rule.
Humberto Bustince mostly deals with Interval valued in his studies of Fuzzy set.
Between 2019 and 2021, his most popular works were:
- The state-of-art of the generalizations of the Choquet integral: From aggregation and pre-aggregation to ordered directionally monotone functions (27 citations)
- Generalized CF1F2-integrals: From Choquet-like aggregation to ordered directionally monotone functions (19 citations)
- A proposal for tuning the $$lpha $$ parameter in $$C_{lpha }C$$CC-integrals for application in fuzzy rule-based classification systems (17 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Real number
Humberto Bustince mainly investigates Choquet integral, Fuzzy logic, Fuzzy set, Fuzzy rule and Artificial intelligence.
He combines subjects such as Christian ministry and Pure mathematics with his study of Choquet integral.
His Fuzzy logic study focuses on Interval valued in particular.
His Fuzzy set study incorporates themes from Image processing, Algorithm, Conjunction and Degree.
His Fuzzy rule research focuses on Characterization and how it relates to Associative property, Theoretical computer science and Class.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Pattern recognition.
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