What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
The scientist’s investigation covers issues in Metaheuristic, Benchmark, Artificial neural network, Differential evolution and Algorithm.
His Metaheuristic research incorporates themes from Swarm behaviour, Image, Thresholding, Multi-objective optimization and Pattern recognition.
His Benchmark research is multidisciplinary, incorporating perspectives in Optimization algorithm, Optimization problem and Particle swarm optimization.
Artificial intelligence covers Mohamed Abd Elaziz research in Artificial neural network.
As part of one scientific family, Mohamed Abd Elaziz deals mainly with the area of Differential evolution, narrowing it down to issues related to the Local search, and often Search algorithm and Heuristic.
The concepts of his Algorithm study are interwoven with issues in Salp swarm algorithm and Feature selection.
His most cited work include:
- An improved Opposition-Based Sine Cosine Algorithm for global optimization (120 citations)
- Modeling of solar energy systems using artificial neural network: A comprehensive review (118 citations)
- Modeling of solar energy systems using artificial neural network: A comprehensive review (118 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Pattern recognition, Algorithm, Feature selection and Image segmentation.
Mohamed Abd Elaziz combines subjects such as Optimization problem and Machine learning with his study of Artificial intelligence.
His work on Segmentation and Feature extraction as part of general Pattern recognition research is often related to Fractal, thus linking different fields of science.
As a part of the same scientific family, Mohamed Abd Elaziz mostly works in the field of Algorithm, focusing on Fitness function and, on occasion, Search algorithm.
He has included themes like Thresholding and Grayscale in his Image segmentation study.
His research in Metaheuristic intersects with topics in Salp swarm algorithm, Swarm behaviour and Benchmark.
He most often published in these fields:
- Artificial intelligence (63.92%)
- Pattern recognition (36.60%)
- Algorithm (30.41%)
What were the highlights of his more recent work (between 2020-2021)?
- Metaheuristic (25.77%)
- Artificial intelligence (63.92%)
- Optimization problem (21.65%)
In recent papers he was focusing on the following fields of study:
Mohamed Abd Elaziz focuses on Metaheuristic, Artificial intelligence, Optimization problem, Algorithm and Benchmark.
His Metaheuristic research incorporates elements of Image processing, Particle swarm optimization and Local search.
His biological study spans a wide range of topics, including Machine learning and Pattern recognition.
The study incorporates disciplines such as Swarm behaviour, Soar and MATLAB in addition to Optimization problem.
Mohamed Abd Elaziz has researched Algorithm in several fields, including Mean squared error and Convergence.
His Benchmark study combines topics in areas such as Differential evolution, Fitness function and Search algorithm.
Between 2020 and 2021, his most popular works were:
- The Arithmetic Optimization Algorithm (33 citations)
- The Arithmetic Optimization Algorithm (33 citations)
- Ant Lion Optimizer: A Comprehensive Survey of Its Variants and Applications (25 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
His primary areas of investigation include Optimization problem, Benchmark, Metaheuristic, Swarm behaviour and Artificial intelligence.
His Optimization problem study introduces a deeper knowledge of Algorithm.
His Benchmark research includes themes of Computational complexity theory, Genetic algorithm, Particle swarm optimization and Arithmetic.
His Metaheuristic study incorporates themes from Multiplication and Heuristic.
His studies in Swarm behaviour integrate themes in fields like Image processing, Mathematical sciences, Theoretical computer science and Metaheuristic algorithms.
His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Coefficient of determination.
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