Roohollah Shirani Faradonbeh
Orcid: 0000-0002-1518-3597
According to our database1,
Roohollah Shirani Faradonbeh
authored at least 17 papers
between 2016 and 2024.
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Bibliography
2024
Assessing the shear strength of sandy soil reinforced with polyethylene-terephthalate: an AI-based approach.
Earth Sci. Informatics, October, 2024
Hybridized intelligent multi-class classifiers for rockburst risk assessment in deep underground mines.
Neural Comput. Appl., February, 2024
Enhancing earth dam slope stability prediction with integrated AI and statistical models.
Appl. Soft Comput., 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
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
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
Genetic programing and non-linear multiple regression techniques to predict backbreak in blasting operation.
Eng. Comput., 2016