What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial neural network
- Machine learning
Artificial neural network, Structural engineering, Mean squared error, Sensitivity and Artificial intelligence are his primary areas of study.
His studies deal with areas such as Geotechnical engineering, Coefficient of determination and Particle swarm optimization as well as Artificial neural network.
Masoud Monjezi combines subjects such as Radial basis function neural, General regression neural network and Multi layer perceptron neural network with his study of Structural engineering.
His work focuses on many connections between Mean squared error and other disciplines, such as Algorithm, that overlap with his field of interest in Factor of safety and Slope stability.
His biological study spans a wide range of topics, including Genetic algorithm and Data mining.
His Data mining research incorporates themes from Regression analysis, Point and Forensic engineering.
His most cited work include:
- Evaluation and prediction of blast-induced ground vibration at Shur River Dam, Iran, by artificial neural network (156 citations)
- Prediction of seismic slope stability through combination of particle swarm optimization and neural network (150 citations)
- Prediction of blast-induced ground vibration using artificial neural networks (126 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Artificial neural network, Mean squared error, Artificial intelligence, Geotechnical engineering and Data mining.
The Artificial neural network study combines topics in areas such as Algorithm, Structural engineering and Rock mass classification.
The various areas that Masoud Monjezi examines in his Mean squared error study include Regression analysis, Coefficient of determination and Linear regression.
His work on Hidden layer and Perceptron as part of general Artificial intelligence study is frequently linked to Copper mine and Biological system, therefore connecting diverse disciplines of science.
His work carried out in the field of Geotechnical engineering brings together such families of science as Mining engineering and Schmidt hammer.
Masoud Monjezi has included themes like Empirical modelling and Support vector machine in his Data mining study.
He most often published in these fields:
- Artificial neural network (41.11%)
- Mean squared error (31.11%)
- Artificial intelligence (22.22%)
What were the highlights of his more recent work (between 2017-2021)?
- Coefficient of determination (21.11%)
- Artificial neural network (41.11%)
- Structural engineering (21.11%)
In recent papers he was focusing on the following fields of study:
Masoud Monjezi focuses on Coefficient of determination, Artificial neural network, Structural engineering, Mathematical optimization and Gene expression programming.
His research in Coefficient of determination intersects with topics in Mean squared error, Geotechnical engineering and Artificial intelligence.
In his study, Masoud Monjezi carries out multidisciplinary Artificial neural network and Particle velocity research.
His research integrates issues of Multivariate statistics and Rock mass classification in his study of Structural engineering.
His work on Maximization and Solver as part of general Mathematical optimization research is frequently linked to Environmental impact assessment and Net present value, bridging the gap between disciplines.
His study explores the link between Gene expression programming and topics such as Linear regression that cross with problems in Empirical modelling, Data mining, Genetic programming and Performance prediction.
Between 2017 and 2021, his most popular works were:
- Development of GP and GEP models to estimate an environmental issue induced by blasting operation. (28 citations)
- Optimization of flyrock and rock fragmentation in the Tajareh limestone mine using metaheuristics method of firefly algorithm (27 citations)
- Uniaxial compressive strength prediction through a new technique based on gene expression programming (25 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Machine learning
- Artificial intelligence
Masoud Monjezi spends much of his time researching Coefficient of determination, Mean squared error, Geotechnical engineering, Gene expression programming and Linear regression.
His Coefficient of determination research integrates issues from Firefly algorithm and Metaheuristic.
His Mean squared error research is multidisciplinary, incorporating elements of Decision tree, Structural engineering and Rock mass classification.
His work on Geological Strength Index is typically connected to Computational Science and Engineering, Multiple linear regression analysis, Durability and Experimental methods as part of general Geotechnical engineering study, connecting several disciplines of science.
His work deals with themes such as Empirical modelling, Performance prediction, Genetic programming and Data mining, which intersect with Gene expression programming.
His Variance studies intersect with other disciplines such as Measure, Joint, Multivariate statistics, Statistics and Correlation coefficient.
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