What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Structural engineering
- Statistics
His primary areas of investigation include Mathematical optimization, Metaheuristic, Benchmark, Algorithm and Particle swarm optimization.
Siamak Talatahari works in the field of Mathematical optimization, focusing on Search algorithm in particular.
As a part of the same scientific study, Siamak Talatahari usually deals with the Metaheuristic, concentrating on Ant colony optimization algorithms and frequently concerns with Harmony search and Finite element method.
His Benchmark study incorporates themes from Global optimization and Constrained optimization.
His work on Swarm intelligence and Multi-swarm optimization as part of general Particle swarm optimization study is frequently linked to Dome and Big bang big crunch algorithm, bridging the gap between disciplines.
His work in Optimal design addresses issues such as Topology, which are connected to fields such as Chaos theory.
His most cited work include:
- A novel heuristic optimization method: charged system search (769 citations)
- Firefly algorithm with chaos (484 citations)
- Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures (361 citations)
What are the main themes of his work throughout his whole career to date?
Mathematical optimization, Metaheuristic, Optimal design, Structural engineering and Benchmark are his primary areas of study.
Siamak Talatahari interconnects Algorithm and Truss in the investigation of issues within Mathematical optimization.
His Metaheuristic research is multidisciplinary, incorporating elements of Frame, Harmony search, Ant colony optimization algorithms and Engineering design process.
His Optimal design study integrates concerns from other disciplines, such as Arch and Construction management.
His studies in Structural engineering integrate themes in fields like Robustness and Nonlinear system.
Siamak Talatahari focuses mostly in the field of Benchmark, narrowing it down to topics relating to Global optimization and, in certain cases, Chaotic.
He most often published in these fields:
- Mathematical optimization (58.06%)
- Metaheuristic (38.06%)
- Optimal design (23.87%)
What were the highlights of his more recent work (between 2019-2021)?
- Metaheuristic (38.06%)
- Nonlinear system (26.45%)
- Mathematical optimization (58.06%)
In recent papers he was focusing on the following fields of study:
Siamak Talatahari spends much of his time researching Metaheuristic, Nonlinear system, Mathematical optimization, Benchmark and Structural engineering.
The study incorporates disciplines such as Perspective, Engineering design process and Search algorithm in addition to Metaheuristic.
The Nonlinear system study combines topics in areas such as Optimization algorithm, Control theory and Fuzzy logic.
Siamak Talatahari has included themes like Standard algorithms and Truss in his Mathematical optimization study.
His Finite element method, Shear buckling, Plate girder and High rise study, which is part of a larger body of work in Structural engineering, is frequently linked to Design objective, bridging the gap between disciplines.
His Algorithm research incorporates themes from Optimal design and Standard deviation.
Between 2019 and 2021, his most popular works were:
- Optimum design of fuzzy controller using hybrid ant lion optimizer and Jaya algorithm (19 citations)
- Optimum design of fuzzy controller using hybrid ant lion optimizer and Jaya algorithm (19 citations)
- Optimization of constrained mathematical and engineering design problems using chaos game optimization (14 citations)
In his most recent research, the most cited papers focused on:
- Mathematical optimization
- Statistics
- Structural engineering
The scientist’s investigation covers issues in Metaheuristic, Mathematical optimization, Nonlinear system, Optimization algorithm and Chaos game.
His Metaheuristic research is under the purview of Algorithm.
His Algorithm research includes elements of Structure, Control theory, Fuzzy logic and Benchmark.
His Mathematical optimization study frequently links to other fields, such as Optimal design.
His Nonlinear system research integrates issues from Fuzzy inference system, Adaptive neuro fuzzy inference system and Damper.
His Optimization algorithm study combines topics from a wide range of disciplines, such as Vibration control, Inverse, Merit function and Control theory.
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