What is he best known for?
The fields of study he is best known for:
- Statistics
- Mathematical analysis
- Mathematical optimization
His primary scientific interests are in Uncertainty theory, Mathematical optimization, Mathematical economics, Fuzzy classification and Fuzzy number.
His studies in Uncertainty theory integrate themes in fields like Stochastic differential equation, Uncertainty analysis, Axiom and Differential equation.
His study in Mathematical optimization is interdisciplinary in nature, drawing from both Portfolio optimization, Portfolio and Fuzzy logic.
His Mathematical economics research integrates issues from Credibility theory, Credibility and Subadditivity.
Baoding Liu has researched Fuzzy classification in several fields, including Fuzzy set operations, Random function and Multivariate random variable.
His biological study deals with issues like Defuzzification, which deal with fields such as Fuzzy transportation, Fuzzy mathematics and Fuzzy measure theory.
His most cited work include:
- Expected value of fuzzy variable and fuzzy expected value models (1469 citations)
- Uncertainty Theory (1068 citations)
- Uncertainty Theory: A Branch of Mathematics for Modeling Human Uncertainty (729 citations)
What are the main themes of his work throughout his whole career to date?
Baoding Liu spends much of his time researching Mathematical optimization, Fuzzy logic, Fuzzy number, Fuzzy set operations and Uncertainty theory.
His Genetic algorithm, Stochastic programming and Goal programming study in the realm of Mathematical optimization interacts with subjects such as Reactive programming and Inductive programming.
His Fuzzy logic study incorporates themes from Discrete mathematics, Algorithm and Expected value.
His studies examine the connections between Fuzzy number and genetics, as well as such issues in Multivariate random variable, with regards to Random function and Random element.
His study brings together the fields of Fuzzy classification and Fuzzy set operations.
The Uncertainty theory study combines topics in areas such as Axiom, Uncertainty analysis and Mathematical economics.
He most often published in these fields:
- Mathematical optimization (48.98%)
- Fuzzy logic (37.41%)
- Fuzzy number (26.53%)
What were the highlights of his more recent work (between 2012-2021)?
- Uncertainty theory (19.05%)
- Mathematical economics (11.56%)
- Mathematical optimization (48.98%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Uncertainty theory, Mathematical economics, Mathematical optimization, Computational intelligence and Applied mathematics.
His Uncertainty theory research incorporates elements of Uncertainty analysis, Series and Process.
His Uncertainty analysis research includes elements of Product measure, Axiom, Monotonic function and Subadditivity.
His research investigates the connection between Mathematical economics and topics such as Discrete mathematics that intersect with issues in Membership function, Key and Fuzzy logic.
Borrowing concepts from Production control, he weaves in ideas under Mathematical optimization.
His Applied mathematics study combines topics from a wide range of disciplines, such as Estimation theory, Method of moments and Differential equation.
Between 2012 and 2021, his most popular works were:
- Toward uncertain finance theory (164 citations)
- Extreme value theorems of uncertain process with application to insurance risk model (82 citations)
- Uncertain Multiobjective Programming and Uncertain Goal Programming (66 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Mathematical analysis
- Mathematical optimization
The scientist’s investigation covers issues in Uncertainty theory, Mathematical optimization, Process, Regression analysis and Statistics.
His Uncertainty theory study integrates concerns from other disciplines, such as Genetic algorithm, Mathematical economics, Hierarchical control system, Sequence and Series.
His Mathematical economics research incorporates themes from Stochastic differential equation, Financial market and Extreme value theory.
His research in Mathematical optimization intersects with topics in Control and Product.
The study incorporates disciplines such as Computational intelligence and Differential equation in addition to Process.
The concepts of his Regression analysis study are interwoven with issues in Residual and Confidence interval.
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