Gai-Ge Wang mainly focuses on Metaheuristic, Mathematical optimization, Artificial intelligence, Algorithm and Optimization problem. Gai-Ge Wang works mostly in the field of Metaheuristic, limiting it down to topics relating to Evolutionary computation and, in certain cases, Statistics. His study in the fields of Krill herd algorithm and Meta-optimization under the domain of Mathematical optimization overlaps with other disciplines such as Krill.
His Artificial intelligence study which covers Swarm intelligence that intersects with Search algorithm, Global optimization problem and Metaheuristic optimization. Gai-Ge Wang does research in Algorithm, focusing on Cuckoo search specifically. His work deals with themes such as Genetic algorithm, Harmony search, Global optimization and Benchmark, which intersect with Optimization problem.
Mathematical optimization, Algorithm, Metaheuristic, Optimization problem and Benchmark are his primary areas of study. His study on Knapsack problem, Krill herd algorithm and Local search is often connected to Krill as part of broader study in Mathematical optimization. His work in Algorithm tackles topics such as Harmony search which are related to areas like Optimization methods.
His Metaheuristic study combines topics in areas such as Evolutionary computation, Swarm intelligence, Continuous optimization and Travelling salesman problem. The concepts of his Swarm intelligence study are interwoven with issues in Crossover and Artificial intelligence. His Benchmark study incorporates themes from Global optimization, Biogeography-based optimization and Metaheuristic algorithms.
His scientific interests lie mostly in Algorithm, Mathematical optimization, Optimization problem, Cuckoo search and Evolutionary algorithm. His Algorithm research integrates issues from Fuzzy set, Fuzzy logic and Local area network. His study connects Benchmark and Mathematical optimization.
His study on Benchmark also encompasses disciplines like
His primary scientific interests are in Mathematical optimization, Optimization problem, Evolutionary algorithm, Benchmark and Scale. As part of his studies on Mathematical optimization, he often connects relevant subjects like Theoretical computer science. He has researched Optimization problem in several fields, including Evolutionary computation and B-tree.
His Evolutionary algorithm research incorporates themes from Scale, Sorting and Crossover. He works mostly in the field of Benchmark, limiting it down to concerns involving Selection and, occasionally, Metaheuristic algorithms and Swarm intelligence. His Algorithm study combines topics from a wide range of disciplines, such as Fuzzy set and Evolution strategy.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Chaotic Krill Herd algorithm
Gai-Ge Wang;Lihong Guo;Amir Hossein Gandomi;Guo-sheng Hao.
Information Sciences (2014)
Monarch butterfly optimization
Gai-Ge Wang;Gai-Ge Wang;Suash Deb;Zhihua Cui.
Neural Computing and Applications (2019)
Elephant Herding Optimization
Gai-Ge Wang;Suash Deb;Leandro dos S. Coelho.
2015 3rd International Symposium on Computational and Business Intelligence (ISCBI) (2015)
A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization
Gaige Wang;Lihong Guo.
Journal of Applied Mathematics (2013)
Moth search algorithm: a bio-inspired metaheuristic algorithm for global optimization problems
Gai-Ge Wang;Gai-Ge Wang;Gai-Ge Wang.
Memetic Computing (2018)
A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyberphysical systems
Zhihua Cui;Bin Sun;Gaige Wang;Yu Xue.
Journal of Parallel and Distributed Computing (2017)
Detection of Malicious Code Variants Based on Deep Learning
Zhihua Cui;Fei Xue;Xingjuan Cai;Yang Cao.
IEEE Transactions on Industrial Informatics (2018)
Earthworm optimisation algorithm: a bio-inspired metaheuristic algorithm for global optimisation problems
Gai Ge Wang;Suash Deb;Leandro Dos Santos Coelho.
International Journal of Bio-inspired Computation (2015)
Hybridizing harmony search algorithm with cuckoo search for global numerical optimization
Gai-Ge Wang;Amir H. Gandomi;Xiangjun Zhao;Hai Cheng Chu.
soft computing (2016)
An effective krill herd algorithm with migration operator in biogeography-based optimization
Gai-Ge Wang;Amir H. Gandomi;Amir H. Alavi.
Applied Mathematical Modelling (2014)
Profile was last updated on December 6th, 2021.
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