Danial Jahed Armaghani
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Citado por
Prediction of pile bearing capacity using a hybrid genetic algorithm-based ANN
E Momeni, R Nazir, DJ Armaghani, H Maizir
Measurement 57, 122-131, 2014
Development of hybrid intelligent models for predicting TBM penetration rate in hard rock condition
DJ Armaghani, ET Mohamad, MS Narayanasamy, N Narita, S Yagiz
Tunnelling and Underground Space Technology 63, 29-43, 2017
Blasting-induced flyrock and ground vibration prediction through an expert artificial neural network based on particle swarm optimization
DJ Armaghani, M Hajihassani, ET Mohamad, A Marto, SA Noorani
Arabian Journal of Geosciences 7, 5383-5396, 2014
Prediction of uniaxial compressive strength of rock samples using hybrid particle swarm optimization-based artificial neural networks
E Momeni, DJ Armaghani, M Hajihassani, MFM Amin
Measurement 60, 50-63, 2015
Prediction of seismic slope stability through combination of particle swarm optimization and neural network
B Gordan, D Jahed Armaghani, M Hajihassani, M Monjezi
Engineering with computers 32, 85-97, 2016
A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength
DJ Armaghani, PG Asteris
Neural Computing and Applications 33 (9), 4501-4532, 2021
Feasibility of indirect determination of blast induced ground vibration based on support vector machine
M Hasanipanah, M Monjezi, A Shahnazar, DJ Armaghani, A Farazmand
Measurement 75, 289-297, 2015
Ground vibration prediction in quarry blasting through an artificial neural network optimized by imperialist competitive algorithm
M Hajihassani, DJ Armaghani, A Marto, ET Mohamad
Bull Eng Geol Environ 74 (3), 873-886, 2015
Feasibility of PSO-ANN model for predicting surface settlement caused by tunneling
M Hasanipanah, M Noorian-Bidgoli, D Jahed Armaghani, H Khamesi
Engineering with Computers 32, 705-715, 2016
Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate
J Zhou, Y Qiu, S Zhu, DJ Armaghani, C Li, H Nguyen, S Yagiz
Engineering Applications of Artificial Intelligence 97, 104015, 2021
Prediction of airblast-overpressure induced by blasting using a hybrid artificial neural network and particle swarm optimization
M Hajihassani, DJ Armaghani, H Sohaei, ET Mohamad, A Marto
Applied Acoustics 80, 57-67, 2014
Prediction of the unconfined compressive strength of soft rocks: a PSO-based ANN approach
ET Mohamad, D Jahed Armaghani, E Momeni, ...
Bulletin of Engineering Geology and the Environment 74, 745-757, 2015
Prediction and optimization of back-break and rock fragmentation using an artificial neural network and a bee colony algorithm
E Ebrahimi, M Monjezi, MR Khalesi, DJ Armaghani
Bulletin of Engineering Geology and the Environment 75, 27-36, 2016
Random forests and cubist algorithms for predicting shear strengths of rockfill materials
J Zhou, E Li, H Wei, C Li, Q Qiao, DJ Armaghani
Applied sciences 9 (8), 1621, 2019
Supervised machine learning techniques to the prediction of tunnel boring machine penetration rate
H Xu, J Zhou, P G. Asteris, D Jahed Armaghani, MM Tahir
Applied sciences 9 (18), 3715, 2019
Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques
J Zhou, Y Qiu, DJ Armaghani, W Zhang, C Li, S Zhu, R Tarinejad
Geoscience Frontiers 12 (3), 101091, 2021
Applying various hybrid intelligent systems to evaluate and predict slope stability under static and dynamic conditions
M Koopialipoor, D Jahed Armaghani, A Hedayat, A Marto, B Gordan
Soft Computing 23, 5913-5929, 2019
Developing a hybrid PSO–ANN model for estimating the ultimate bearing capacity of rock-socketed piles
D Jahed Armaghani, RSNSBR Shoib, K Faizi, ASA Rashid
Neural Computing and Applications 28, 391-405, 2017
An adaptive neuro-fuzzy inference system for predicting unconfined compressive strength and Young’s modulus: a study on Main Range granite
D Jahed Armaghani, E Tonnizam Mohamad, E Momeni, ...
Bulletin of engineering geology and the environment 74, 1301-1319, 2015
Application of several optimization techniques for estimating TBM advance rate in granitic rocks
DJ Armaghani, M Koopialipoor, A Marto, S Yagiz
Journal of Rock Mechanics and Geotechnical Engineering 11 (4), 779-789, 2019
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