What is he best known for?
The fields of study he is best known for:
- Statistics
- Thermodynamics
- Machine learning
His primary areas of investigation include Mean squared error, Statistics, Froude number, Artificial neural network and Sensitivity.
His work carried out in the field of Mean squared error brings together such families of science as Coefficient of determination, Firefly optimization and Support vector machine.
The various areas that Hossein Bonakdari examines in his Statistics study include Streamflow and Econometrics.
His Froude number study incorporates themes from Sediment transport, Sediment, Dimensionless quantity, Mathematical analysis and Hydraulic structure.
His research on Artificial neural network frequently connects to adjacent areas such as Applied mathematics.
The Sensitivity study combines topics in areas such as Mathematical optimization, Singular value decomposition and Flow, Discharge coefficient.
His most cited work include:
- Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model (92 citations)
- EVALUATION OF SEDIMENT TRANSPORT IN SEWER USING ARTIFICIAL NEURAL NETWORK (71 citations)
- Gene expression programming to predict the discharge coefficient in rectangular side weirs (71 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Mean squared error, Artificial neural network, Froude number, Flow and Algorithm.
His Mean squared error research is multidisciplinary, incorporating perspectives in Soft computing, Communication channel, Applied mathematics and Sensitivity.
His Artificial neural network study also includes fields such as
- Open-channel flow together with Flow velocity,
- Vector field that intertwine with fields like Simulation.
The concepts of his Froude number study are interwoven with issues in Sediment transport, Dimensionless quantity, Geotechnical engineering, Discharge coefficient and Weir.
Hossein Bonakdari has researched Flow in several fields, including Gene expression programming and Regression.
His study in the fields of Particle swarm optimization under the domain of Algorithm overlaps with other disciplines such as Neuro-fuzzy.
He most often published in these fields:
- Mean squared error (32.56%)
- Artificial neural network (25.19%)
- Froude number (17.83%)
What were the highlights of his more recent work (between 2019-2021)?
- Stochastic modelling (4.65%)
- Froude number (17.83%)
- Discharge coefficient (11.63%)
In recent papers he was focusing on the following fields of study:
Hossein Bonakdari mainly investigates Stochastic modelling, Froude number, Discharge coefficient, Algorithm and Communication channel.
The study incorporates disciplines such as Sediment transport and Mathematical analysis in addition to Froude number.
His Discharge coefficient research incorporates themes from Gene expression programming, Weir and Dimensionless quantity.
His Algorithm research focuses on subjects like Normal distribution, which are linked to Sanitary sewer.
His research in Communication channel focuses on subjects like Uncertainty analysis, which are connected to Principle of maximum entropy.
His research integrates issues of Correlation coefficient and Sensitivity in his study of Mean squared error.
Between 2019 and 2021, his most popular works were:
- Evaluation of preprocessing techniques for improving the accuracy of stochastic rainfall forecast models (12 citations)
- Integrative stochastic model standardization with genetic algorithm for rainfall pattern forecasting in tropical and semi-arid environments (11 citations)
- Exploring the Role of Advertising Types on Improving the Water Consumption Behavior: An Application of Integrated Fuzzy AHP and Fuzzy VIKOR Method (11 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Thermodynamics
- Geometry
His scientific interests lie mostly in Communication channel, Uncertainty analysis, Algorithm, Artificial neural network and Stochastic modelling.
His Communication channel study integrates concerns from other disciplines, such as Classification methods, Froude number and Multilayer perceptron.
His study in Algorithm is interdisciplinary in nature, drawing from both Basis, Extreme learning machine, Sanitary sewer, Normal distribution and Vector field.
His work investigates the relationship between Artificial neural network and topics such as Series that intersect with problems in Artificial intelligence.
Hossein Bonakdari works on Statistics which deals in particular with Mean squared error.
Hossein Bonakdari has included themes like Soil science, Sediment transport, Sediment and Sensitivity in his Mean squared error study.
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