What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
His main research concerns Artificial intelligence, Algorithm, Evolutionary computation, Benchmark and Evolutionary algorithm.
His Artificial intelligence research includes themes of Swarm intelligence, Machine learning and Optimisation algorithm.
His Algorithm research is multidisciplinary, incorporating elements of Stability and Adaptive neuro fuzzy inference system.
Xiao-Zhi Gao combines subjects such as Optimization problem and Particle swarm optimization with his study of Evolutionary computation.
His work deals with themes such as Bat algorithm, Swarm behaviour, Multi-swarm optimization and Metaheuristic, which intersect with Benchmark.
His Multi-swarm optimization study integrates concerns from other disciplines, such as Reducer, Hybrid algorithm and Robustness.
His most cited work include:
- A New Bio-inspired Algorithm: Chicken Swarm Optimization (224 citations)
- A New Bio-inspired Algorithm: Chicken Swarm Optimization (224 citations)
- A new bio-inspired optimisation algorithm: Bird Swarm Algorithm (161 citations)
What are the main themes of his work throughout his whole career to date?
Artificial intelligence, Mathematical optimization, Control theory, Fuzzy logic and Fuzzy control system are his primary areas of study.
The concepts of his Artificial intelligence study are interwoven with issues in Algorithm, Machine learning and Pattern recognition.
His work is dedicated to discovering how Algorithm, Swarm behaviour are connected with Swarm intelligence and other disciplines.
As a part of the same scientific study, he usually deals with the Mathematical optimization, concentrating on Benchmark and frequently concerns with Metaheuristic.
In his research, Fuzzy set operations is intimately related to Defuzzification, which falls under the overarching field of Fuzzy control system.
His work on Soft computing and Backpropagation as part of general Artificial neural network research is frequently linked to Fault detection and isolation, thereby connecting diverse disciplines of science.
He most often published in these fields:
- Artificial intelligence (32.16%)
- Mathematical optimization (22.61%)
- Control theory (20.14%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (32.16%)
- Algorithm (15.19%)
- Pattern recognition (8.83%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Artificial intelligence, Algorithm, Pattern recognition, Mathematical optimization and Swarm behaviour.
His studies deal with areas such as Multi-objective optimization and Machine learning as well as Artificial intelligence.
His Algorithm research is multidisciplinary, incorporating perspectives in Evolutionary algorithm, Pareto principle, Encryption and Chaotic.
His studies in Mathematical optimization integrate themes in fields like Optimal design and Reliability.
He interconnects Swarm intelligence, Optimization problem, Vehicle routing problem and Benchmark in the investigation of issues within Swarm behaviour.
His Benchmark study incorporates themes from Genetic algorithm, Clonal selection algorithm and Metaheuristic.
Between 2018 and 2021, his most popular works were:
- Binary differential evolution with self-learning for multi-objective feature selection (73 citations)
- An Enhanced MSIQDE Algorithm With Novel Multiple Strategies for Global Optimization Problems (42 citations)
- MPPCEDE: Multi-population parallel co-evolutionary differential evolution for parameter optimization (32 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
The scientist’s investigation covers issues in Swarm behaviour, Mathematical optimization, Benchmark, Optimization problem and Artificial intelligence.
His biological study spans a wide range of topics, including Swarm intelligence, Vehicle routing problem, Parametric statistics and Industrial engineering.
His work carried out in the field of Mathematical optimization brings together such families of science as Skew, Statistical hypothesis testing, Chaotic and Composite laminates.
His Benchmark study combines topics in areas such as Clonal selection algorithm, Computational intelligence and Group technology.
His study looks at the intersection of Optimization problem and topics like Local optimum with Evolutionary algorithm.
His research integrates issues of Machine learning and Pattern recognition in his study of Artificial intelligence.
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