What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Programming language
His primary areas of study are Artificial intelligence, Fuzzy logic, Machine learning, Data mining and Fuzzy set operations.
His Artificial intelligence study combines topics in areas such as Set and Pattern recognition.
His work on Fuzzy control system as part of general Fuzzy logic study is frequently linked to Granular computing, therefore connecting diverse disciplines of science.
His biological study spans a wide range of topics, including Black-box testing, Oracle and Database.
His Data mining research is multidisciplinary, incorporating elements of Software verification and validation and Software construction.
The Fuzzy set operations study combines topics in areas such as Fuzzy number, Defuzzification and Fuzzy classification.
His most cited work include:
- Fuzzy Mathematical Techniques With Applications (579 citations)
- Fuzzy Expert Systems (532 citations)
- Complex fuzzy sets (280 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Artificial intelligence, Fuzzy logic, Fuzzy set operations, Fuzzy classification and Fuzzy number.
His research integrates issues of Machine learning, Data mining and Pattern recognition in his study of Artificial intelligence.
His research in Data mining intersects with topics in Information retrieval and Cluster analysis.
His study in Fuzzy logic is interdisciplinary in nature, drawing from both Discrete mathematics and Algorithm.
Fuzzy set operations connects with themes related to Fuzzy rule in his study.
He interconnects Fuzzy measure theory, Type-2 fuzzy sets and systems and Membership function in the investigation of issues within Defuzzification.
He most often published in these fields:
- Artificial intelligence (45.89%)
- Fuzzy logic (43.77%)
- Fuzzy set operations (21.49%)
What were the highlights of his more recent work (between 2006-2020)?
- Artificial intelligence (45.89%)
- Fuzzy logic (43.77%)
- Data mining (21.49%)
In recent papers he was focusing on the following fields of study:
Abraham Kandel mainly focuses on Artificial intelligence, Fuzzy logic, Data mining, Theoretical computer science and Fuzzy set.
The study incorporates disciplines such as Machine learning, Computer vision and Pattern recognition in addition to Artificial intelligence.
His Fuzzy logic study frequently intersects with other fields, such as Algorithm.
His Data mining study incorporates themes from Information retrieval, Series and Cluster analysis, Fuzzy clustering.
His studies deal with areas such as Artificial neural network and Management science as well as Fuzzy set.
His Fuzzy set operations study which covers Defuzzification that intersects with Type-2 fuzzy sets and systems and T-norm fuzzy logics.
Between 2006 and 2020, his most popular works were:
- Real-time data mining of non-stationary data streams from sensor networks (63 citations)
- A new interpretation of complex membership grade (54 citations)
- Axiomatic Theory of Complex Fuzzy Logic and Complex Fuzzy Classes (47 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Programming language
His scientific interests lie mostly in Artificial intelligence, Fuzzy logic, Algorithm, Data mining and Theoretical computer science.
He does research in Artificial intelligence, focusing on Fuzzy set specifically.
His specific area of interest is Fuzzy logic, where Abraham Kandel studies Fuzzy control system.
The concepts of his Data mining study are interwoven with issues in Correlation clustering, Cluster analysis, Fuzzy clustering and Trading strategy.
His Theoretical computer science research includes elements of Fuzzy number, Defuzzification, Fuzzy classification, Type-2 fuzzy sets and systems and Fuzzy set operations.
His work carried out in the field of Defuzzification brings together such families of science as Fuzzy mathematics and Membership function.
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