What is he best known for?
The fields of study he is best known for:
- Statistics
- Composite material
- Mathematical optimization
The scientist’s investigation covers issues in Nonlinear system, Robustness, First-order reliability method, Mathematical optimization and Conjugate gradient method.
His study in Nonlinear system is interdisciplinary in nature, drawing from both Mean squared error, Polynomial and Applied mathematics.
His First-order reliability method study combines topics from a wide range of disciplines, such as Control theory, Chaotic, Algorithm, Conjugate and Conjugate residual method.
His work carried out in the field of Mathematical optimization brings together such families of science as Probabilistic logic and Topology optimization.
The study incorporates disciplines such as Distribution and Aluminium in addition to Probabilistic logic.
His Conjugate gradient method research is multidisciplinary, incorporating elements of Sensitivity, Computation, Statistical model and Dimensionality reduction.
His most cited work include:
- Adaptive conjugate single-loop method for efficient reliability-based design and topology optimization (66 citations)
- Comparison of four heuristic regression techniques in solar radiation modeling: Kriging method vs RSM, MARS and M5 model tree (63 citations)
- A hybrid relaxed first-order reliability method for efficient structural reliability analysis (62 citations)
What are the main themes of his work throughout his whole career to date?
Behrooz Keshtegar spends much of his time researching Nonlinear system, Robustness, Structural engineering, Mathematical optimization and Algorithm.
Behrooz Keshtegar interconnects Artificial neural network, Mathematical model and Applied mathematics in the investigation of issues within Nonlinear system.
His Robustness research is multidisciplinary, relying on both Conjugate, Probabilistic logic, Reliability based design and Reliability methods.
His Structural engineering research integrates issues from Reliability and Harmony search.
His research in Mathematical optimization intersects with topics in Computation, Kriging and Benchmark.
His Algorithm study incorporates themes from First-order reliability method, Structural reliability, Support vector machine and Gradient descent.
He most often published in these fields:
- Nonlinear system (33.88%)
- Robustness (26.45%)
- Structural engineering (24.79%)
What were the highlights of his more recent work (between 2020-2021)?
- Artificial neural network (17.36%)
- Structural engineering (24.79%)
- Nonlinear system (33.88%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial neural network, Structural engineering, Nonlinear system, Support vector machine and Robustness.
His Structural engineering research incorporates themes from Harmony search and Hybrid machine.
Behrooz Keshtegar has included themes like Bar, Pitting corrosion, Sensitivity, Exponential function and Reliability in his Nonlinear system study.
The concepts of his Reliability study are interwoven with issues in Probabilistic logic and Latin hypercube sampling.
Behrooz Keshtegar combines subjects such as Mathematical optimization and Heuristic with his study of Support vector machine.
His research investigates the connection between Robustness and topics such as Conjugate that intersect with problems in Conjugate gradient method, Reliability methods and Complex system.
Between 2020 and 2021, his most popular works were:
- Reliability-based structural design optimization: hybridized conjugate mean value approach (18 citations)
- Probabilistic modeling of uncertainties in fatigue reliability analysis of turbine bladed disks (15 citations)
- Multi-extremum-modified response basis model for nonlinear response prediction of dynamic turbine blisk (10 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Composite material
- Machine learning
His main research concerns Sensitivity, Nonlinear system, Exponential function, Artificial neural network and Mathematical optimization.
He has researched Sensitivity in several fields, including Polynomial basis and Surrogate model.
Behrooz Keshtegar undertakes interdisciplinary study in the fields of Nonlinear system and Shear strength through his research.
His research integrates issues of Hyperbolic function and Kriging in his study of Exponential function.
The various areas that he examines in his Artificial neural network study include Swarm behaviour and Support vector machine.
His Mathematical optimization study integrates concerns from other disciplines, such as Conjugate, Robustness and Reliability methods.
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