What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Machine learning
His main research concerns Control theory, Artificial neural network, Nonlinear system, Stability and Exponential stability.
His work deals with themes such as Control engineering and Bounded function, which intersect with Control theory.
His Artificial neural network study deals with the bigger picture of Artificial intelligence.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Pattern recognition.
His work carried out in the field of Nonlinear system brings together such families of science as Gradient descent, Algorithm, Algebraic Riccati equation and Fuzzy control system.
His Stability study incorporates themes from Fuzzy number, Fuzzy set operations and System identification.
His most cited work include:
- Fuzzy identification using fuzzy neural networks with stable learning algorithms (233 citations)
- Nonlinear adaptive trajectory tracking using dynamic neural networks (165 citations)
- Nonlinear system identification using discrete-time recurrent neural networks with stable learning algorithms (144 citations)
What are the main themes of his work throughout his whole career to date?
Wen Yu spends much of his time researching Control theory, Artificial neural network, Artificial intelligence, Nonlinear system and Fuzzy logic.
His studies examine the connections between Control theory and genetics, as well as such issues in Control engineering, with regards to Control.
In his study, which falls under the umbrella issue of Artificial neural network, Vibration is strongly linked to Algorithm.
The concepts of his Artificial intelligence study are interwoven with issues in Machine learning, Data mining and Pattern recognition.
Wen Yu has included themes like Gradient descent, Bounded function, Robustness and System identification in his Nonlinear system study.
His study in Neuro-fuzzy is interdisciplinary in nature, drawing from both Fuzzy number, Fuzzy set operations and Adaptive neuro fuzzy inference system.
He most often published in these fields:
- Control theory (46.56%)
- Artificial neural network (39.47%)
- Artificial intelligence (32.37%)
What were the highlights of his more recent work (between 2018-2021)?
- Control theory (46.56%)
- Artificial neural network (39.47%)
- Artificial intelligence (32.37%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Control theory, Artificial neural network, Artificial intelligence, Nonlinear system and Reinforcement learning.
His studies deal with areas such as Robot and Admittance as well as Control theory.
He interconnects Feature vector, Stewart platform, Benchmark, Workspace and Algorithm in the investigation of issues within Artificial neural network.
The various areas that he examines in his Artificial intelligence study include Data modeling, Machine learning and Pattern recognition.
Wen Yu combines subjects such as Recurrent neural network, Takagi sugeno, Applied mathematics, Fuzzy logic and Robustness with his study of Nonlinear system.
His Reinforcement learning research integrates issues from Robust control and Optimal control.
Between 2018 and 2021, his most popular works were:
- Online Vehicle Routing With Neural Combinatorial Optimization and Deep Reinforcement Learning (30 citations)
- Numerical methods for solving fuzzy equations: a survey (12 citations)
- Control of Flow Rate in Pipeline Using PID Controller (11 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Machine learning
His primary scientific interests are in Control theory, Reinforcement learning, Artificial neural network, Nonlinear system and Fuzzy logic.
The study of Control theory is intertwined with the study of Admittance in a number of ways.
His work investigates the relationship between Reinforcement learning and topics such as Robot that intersect with problems in Control.
Artificial neural network is a subfield of Artificial intelligence that Wen Yu tackles.
His Nonlinear system research incorporates elements of Dual, Fuzzy control system, Fuzzy differential equations, Applied mathematics and Numerical analysis.
His study in the fields of Neuro-fuzzy and Fuzzy set under the domain of Fuzzy logic overlaps with other disciplines such as Control and Z number.
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