2022 - Research.com Rising Star of Science Award
Hossein Moayedi spends much of his time researching Artificial neural network, Mean squared error, Particle swarm optimization, Pile and Landslide. His studies deal with areas such as Bearing capacity, Coefficient of determination and Support vector machine as well as Artificial neural network. Hossein Moayedi combines subjects such as Genetic algorithm, Factor of safety and Metaheuristic with his study of Mean squared error.
His study looks at the relationship between Particle swarm optimization and topics such as Network model, which overlap with Stiffness, Deflection, Seismic loading, Bending stiffness and Data collection. The Pile portion of his research involves studies in Geotechnical engineering and Structural engineering. His work in the fields of Landslide, such as Topographic Wetness Index, intersects with other areas such as Spatial database.
His primary scientific interests are in Artificial neural network, Geotechnical engineering, Mean squared error, Algorithm and Metaheuristic. The study incorporates disciplines such as Particle swarm optimization, Coefficient of determination and Bearing capacity in addition to Artificial neural network. His Geotechnical engineering research includes elements of Soil water, Finite element method and Cement.
As a part of the same scientific family, Hossein Moayedi mostly works in the field of Mean squared error, focusing on Factor of safety and, on occasion, Slope stability analysis. His study looks at the intersection of Algorithm and topics like Multilayer perceptron with Evolution strategy. In his work, Data mining is strongly intertwined with Landslide, which is a subfield of Metaheuristic.
Hossein Moayedi mostly deals with Artificial neural network, Algorithm, Mean squared error, Metaheuristic and Perceptron. His Artificial neural network research is included under the broader classification of Artificial intelligence. His Algorithm study also includes
His Mean squared error research includes themes of Factor of safety, Genetic algorithm and Network model. His Genetic algorithm research incorporates elements of Particle swarm optimization and Data mining. His work in the fields of Metaheuristic algorithms overlaps with other areas such as Adaptive neuro fuzzy inference system.
Hossein Moayedi focuses on Artificial neural network, Mean squared error, Particle swarm optimization, Perceptron and Algorithm. Hossein Moayedi interconnects Bearing capacity, Quadratic classifier, Support vector machine and Metaheuristic in the investigation of issues within Artificial neural network. The concepts of his Mean squared error study are interwoven with issues in Genetic algorithm, Glazing and Sensitivity.
The Particle swarm optimization study combines topics in areas such as Evolutionary algorithm, Slope stability and Structural engineering. His biological study spans a wide range of topics, including Ensemble forecasting and Cooling load. His Algorithm research incorporates themes from Evolutionary data mining, Poisson distribution and Dragonfly algorithm.
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.
Green synthesis using cherry and orange juice and characterization of TbFeO3 ceramic nanostructures and their application as photocatalysts under UV light for removal of organic dyes in water
Pourya Mehdizadeh;Yasin Orooji;Omid Amiri;Masoud Salavati-Niasari.
Journal of Cleaner Production (2020)
Modification of landslide susceptibility mapping using optimized PSO-ANN technique
Hossein Moayedi;Mohammad Mehrabi;Mansour Mosallanezhad;Ahmad Safuan A. Rashid.
Engineering With Computers (2019)
Modelling and optimization of ultimate bearing capacity of strip footing near a slope by soft computing methods
Hossein Moayedi;Sajad Hayati.
Applied Soft Computing (2018)
A spatially explicit deep learning neural network model for the prediction of landslide susceptibility
Dong Van Dao;Abolfazl Jaafari;Mahmoud Bayat;Davood Mafi-Gholami.
Catena (2020)
An artificial neural network approach for under-reamed piles subjected to uplift forces in dry sand
Hossein Moayedi;Abbas Rezaei.
Neural Computing and Applications (2019)
Applicability of a CPT-Based Neural Network Solution in Predicting Load-Settlement Responses of Bored Pile
Hossein Moayedi;Sajad Hayati.
International Journal of Geomechanics (2018)
Optimizing an ANN model with ICA for estimating bearing capacity of driven pile in cohesionless soil
Hossein Moayedi;Danial Jahed Armaghani.
Engineering With Computers (2018)
Optimization of ANFIS with GA and PSO estimating α ratio in driven piles
Hossein Moayedi;Mehdi Raftari;Abolhasan Sharifi;Wan Amizah Wan Jusoh.
Engineering With Computers (2020)
Novel Soft Computing Model for Predicting Blast-Induced Ground Vibration in Open-Pit Mines Based on Particle Swarm Optimization and XGBoost
Xiliang Zhang;Hoang Nguyen;Xuan-Nam Bui;Quang-Hieu Tran.
Natural resources research (2020)
Free vibration analysis of an electro-elastic GPLRC cylindrical shell surrounded by viscoelastic foundation using modified length-couple stress parameter
Aria Ghabussi;Negin Ashrafi;Aghil Shavalipour;Abolfazl Hosseinpour.
Mechanics Based Design of Structures and Machines (2021)
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