What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Artificial intelligence
- Metaheuristic
The scientist’s investigation covers issues in Mathematical optimization, Sizing, Identification, Hybrid system and Harmony search.
His study in Mathematical optimization concentrates on Metaheuristic, Multi-swarm optimization and Metaheuristic optimization.
The study incorporates disciplines such as Local optimum and Optimization problem in addition to Metaheuristic.
Borrowing concepts from Focus, Alireza Askarzadeh weaves in ideas under Harmony search.
He has researched Particle swarm optimization in several fields, including Estimation theory, Robustness and Nonlinear system.
His research integrates issues of Decision variables, Crow search algorithm and Engineering optimization in his study of Artificial intelligence.
His most cited work include:
- A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm (713 citations)
- Artificial bee swarm optimization algorithm for parameters identification of solar cell models (242 citations)
- Parameter identification for solar cell models using harmony search-based algorithms (241 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Mathematical optimization, Optimization problem, Particle swarm optimization, Harmony search and Metaheuristic.
His Mathematical optimization study combines topics from a wide range of disciplines, such as Hybrid system and Electric power system.
His Optimization problem research integrates issues from Local optimum, Electric power, Simulation and Benchmark.
His Multi-swarm optimization study in the realm of Particle swarm optimization interacts with subjects such as Proton exchange membrane fuel cell.
His study in Harmony search is interdisciplinary in nature, drawing from both Mean absolute percentage error and Heuristic.
The Metaheuristic study combines topics in areas such as Differential evolution and Capacitor.
He most often published in these fields:
- Mathematical optimization (50.00%)
- Optimization problem (32.35%)
- Particle swarm optimization (32.35%)
What were the highlights of his more recent work (between 2018-2020)?
- Mathematical optimization (50.00%)
- Diesel generator (11.76%)
- Distribution networks (7.35%)
In recent papers he was focusing on the following fields of study:
His main research concerns Mathematical optimization, Diesel generator, Distribution networks, Hybrid system and Multi-objective optimization.
Alireza Askarzadeh is studying Particle swarm optimization, which is a component of Mathematical optimization.
His Particle swarm optimization research is multidisciplinary, incorporating perspectives in Genetic algorithm and Electric power system.
His Distribution networks study also includes
- Crow search algorithm which intersects with area such as Reliability engineering,
- Minification that connect with fields like Control theory.
His work on Diesel fuel as part of general Automotive engineering research is frequently linked to Hydrogen fuel, bridging the gap between disciplines.
In his work, Reduction is strongly intertwined with Optimization problem, which is a subfield of Diesel fuel.
Between 2018 and 2020, his most popular works were:
- Techno-economic analysis and size optimization of an off-grid hybrid photovoltaic, fuel cell and diesel generator system (80 citations)
- Optimizing operation of a photovoltaic/diesel generator hybrid energy system with pumped hydro storage by a modified crow search algorithm (28 citations)
- Size and power exchange optimization of a grid-connected diesel generator-photovoltaic-fuel cell hybrid energy system considering reliability, cost and renewability (21 citations)
In his most recent research, the most cited papers focused on:
- Mathematical optimization
- Artificial intelligence
- Genetic algorithm
The scientist’s investigation covers issues in Automotive engineering, Diesel generator, Diesel fuel, Cost of electricity by source and Hybrid system.
His studies in Automotive engineering integrate themes in fields like Pumped-storage hydroelectricity, Multi-objective optimization and Optimization problem.
His work deals with themes such as Genetic algorithm, Particle swarm optimization and Fuel efficiency, which intersect with Pumped-storage hydroelectricity.
Diesel generator connects with themes related to Solar power in his study.
His Solar power research includes elements of Operating reserve and Electric power.
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