H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology H-index 35 Citations 4,338 195 World Ranking 3547 National Ranking 2

Overview

What is he best known for?

The fields of study he is best known for:

  • Thermodynamics
  • Composite material
  • Geotechnical engineering

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 most cited work include:

  • Modelling and optimization of ultimate bearing capacity of strip footing near a slope by soft computing methods (97 citations)
  • Modification of landslide susceptibility mapping using optimized PSO-ANN technique (96 citations)
  • Applicability of a CPT-Based Neural Network Solution in Predicting Load-Settlement Responses of Bored Pile (85 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Artificial neural network (25.31%)
  • Geotechnical engineering (21.58%)
  • Mean squared error (14.11%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial neural network (25.31%)
  • Algorithm (11.20%)
  • Mean squared error (14.11%)

In recent papers he was focusing on the following fields of study:

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

  • Bearing capacity which is related to area like Settlement, Soil water, Foundation and Finite element method,
  • Range which is related to area like Embedment.

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.

Between 2019 and 2021, his most popular works were:

  • 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 (71 citations)
  • Optimization of ANFIS with GA and PSO estimating α ratio in driven piles (66 citations)
  • A spatially explicit deep learning neural network model for the prediction of landslide susceptibility (59 citations)

In his most recent research, the most cited papers focused on:

  • Thermodynamics
  • Composite material
  • Statistics

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.

Top Publications

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)

145 Citations

Modification of landslide susceptibility mapping using optimized PSO-ANN technique

Hossein Moayedi;Mohammad Mehrabi;Mansour Mosallanezhad;Ahmad Safuan A. Rashid.
Engineering With Computers (2019)

137 Citations

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)

120 Citations

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)

105 Citations

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)

99 Citations

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)

98 Citations

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)

96 Citations

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)

87 Citations

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)

86 Citations

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)

84 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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