What is he best known for?
The fields of study he is best known for:
- Mechanical engineering
- Chemical engineering
- Artificial neural network
The scientist’s investigation covers issues in Artificial neural network, Pulmonary surfactant, Enhanced oil recovery, Particle swarm optimization and Petroleum engineering.
His studies in Artificial neural network integrate themes in fields like Evolutionary algorithm, Genetic algorithm, Asphaltene and Fuzzy logic.
His Genetic algorithm research integrates issues from Kalman filter, Control theory, Dew point and Reservoir simulation.
His Fuzzy logic research is multidisciplinary, incorporating elements of Support vector machine and Robustness.
His Enhanced oil recovery research incorporates themes from Microemulsion, Surface tension and Brine.
Mohammad Ali Ahmadi works mostly in the field of Particle swarm optimization, limiting it down to topics relating to Permeability and, in certain cases, Mathematical optimization and Multi-swarm optimization.
His most cited work include:
- Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir (189 citations)
- Prediction carbon dioxide solubility in presence of various ionic liquids using computational intelligence approaches (146 citations)
- Reservoir permeability prediction by neural networks combined with hybrid genetic algorithm and particle swarm optimization (137 citations)
What are the main themes of his work throughout his whole career to date?
Mohammad Ali Ahmadi spends much of his time researching Petroleum engineering, Artificial neural network, Genetic algorithm, Enhanced oil recovery and Particle swarm optimization.
His Petroleum engineering research is multidisciplinary, relying on both Dew point and Porous medium.
His work carried out in the field of Artificial neural network brings together such families of science as Asphaltene, Support vector machine and Fuzzy logic.
His research in Genetic algorithm intersects with topics in Thermal conductivity and Relative permeability.
In Enhanced oil recovery, Mohammad Ali Ahmadi works on issues like Pulmonary surfactant, which are connected to Nanoparticle and Surface tension.
His Multi-swarm optimization study in the realm of Particle swarm optimization connects with subjects such as Biological system.
He most often published in these fields:
- Petroleum engineering (31.25%)
- Artificial neural network (31.25%)
- Genetic algorithm (22.32%)
What were the highlights of his more recent work (between 2015-2020)?
- Petroleum engineering (31.25%)
- Genetic algorithm (22.32%)
- Enhanced oil recovery (19.64%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Petroleum engineering, Genetic algorithm, Enhanced oil recovery, Mathematical optimization and Heat engine.
His Petroleum engineering study combines topics in areas such as Dew point, Coefficient of determination, Data mining and Least squares support vector machine.
His biological study spans a wide range of topics, including Artificial neural network and Thermal conductivity.
His Artificial neural network study frequently intersects with other fields, such as Particle swarm optimization.
His research in Enhanced oil recovery intersects with topics in Water injection and Pulmonary surfactant.
His study on Mathematical optimization also encompasses disciplines like
- Sorting which connect with Dimensionless quantity and Rankine cycle,
- TOPSIS which intersects with area such as Fuzzy logic, Evolutionary algorithm and Multi-objective optimization,
- Coefficient of performance that intertwine with fields like Refrigeration.
Between 2015 and 2020, his most popular works were:
- Thermodynamic analysis and multi objective optimization of performance of solar dish Stirling engine by the centrality of entransy and entropy generation (95 citations)
- A proposed model to predict thermal conductivity ratio of Al 2 O 3 /EG nanofluid by applying least squares support vector machine (LSSVM) and genetic algorithm as a connectionist approach (79 citations)
- Multi objective optimization of performance of three-heat-source irreversible refrigerators based algorithm NSGAII (67 citations)
In his most recent research, the most cited papers focused on:
- Mechanical engineering
- Chemical engineering
- Artificial intelligence
His primary areas of investigation include Multi-objective optimization, Mean squared error, Stirling engine, Mechanical engineering and Genetic algorithm.
His Multi-objective optimization research is included under the broader classification of Mathematical optimization.
Mohammad Ali Ahmadi interconnects Sorting, Carnot cycle, Simulation and Fuzzy logic in the investigation of issues within Mathematical optimization.
His work on Stirling cycle and Ericsson cycle is typically connected to Thermal efficiency as part of general Stirling engine study, connecting several disciplines of science.
His Mechanical engineering study combines topics from a wide range of disciplines, such as Automotive engineering and Heat transfer.
His Genetic algorithm research integrates issues from Power, Least squares support vector machine, Coefficient of determination, Applied mathematics and Hyperparameter.
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.
