Roohollah Shirani Faradonbeh

Orcid: 0000-0002-1518-3597

According to our database1, Roohollah Shirani Faradonbeh authored at least 15 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
Hybridized intelligent multi-class classifiers for rockburst risk assessment in deep underground mines.
Neural Comput. Appl., February, 2024

2020
Application of self-organizing map and fuzzy c-mean techniques for rockburst clustering in deep underground projects.
Neural Comput. Appl., 2020

2019
Long-term prediction of rockburst hazard in deep underground openings using three robust data mining techniques.
Eng. Comput., 2019

2018
Prediction and minimization of blast-induced flyrock using gene expression programming and firefly algorithm.
Neural Comput. Appl., 2018

Settlement prediction of the rock-socketed piles through a new technique based on gene expression programming.
Neural Comput. Appl., 2018

Performance prediction of tunnel boring machine through developing a gene expression programming equation.
Eng. Comput., 2018

2017
An optimized ANN model based on genetic algorithm for predicting ripping production.
Neural Comput. Appl., 2017

Function development for appraising brittleness of intact rocks using genetic programming and non-linear multiple regression models.
Eng. Comput., 2017

Classification and regression tree technique in estimating peak particle velocity caused by blasting.
Eng. Comput., 2017

Forecasting blast-induced ground vibration developing a CART model.
Eng. Comput., 2017

Prediction and minimization of blast-induced ground vibration using two robust meta-heuristic algorithms.
Eng. Comput., 2017

2016
Combination of neural network and ant colony optimization algorithms for prediction and optimization of flyrock and back-break induced by blasting.
Eng. Comput., 2016

Modification and prediction of blast-induced ground vibrations based on both empirical and computational techniques.
Eng. Comput., 2016

Rock strength assessment based on regression tree technique.
Eng. Comput., 2016

Genetic programing and non-linear multiple regression techniques to predict backbreak in blasting operation.
Eng. Comput., 2016


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