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Hamid Kalhori
Hamid Kalhori
Department of Mining Engineering, Isfahan University of Technology
在 mi.iut.ac.ir 的电子邮件经过验证
标题
引用次数
引用次数
年份
Application of carbonate precipitating bacteria for improving properties and repairing cracks of shotcrete
H Kalhori, R Bagherpour
Construction and Building Materials 148, 249-260, 2017
1582017
A new hybrid ANFIS–PSO model for prediction of peak particle velocity due to bench blasting
E Ghasemi, H Kalhori, R Bagherpour
Engineering with Computers 32, 607-614, 2016
992016
Model tree approach for predicting uniaxial compressive strength and Young’s modulus of carbonate rocks
E Ghasemi, H Kalhori, R Bagherpour, S Yagiz
Bulletin of Engineering Geology and the Environment, 1-13, 2016
832016
Application of bacterial nanocellulose fibers as reinforcement in cement composites
MA Akhlaghi, R Bagherpour, H Kalhori
Construction and Building Materials 241, 118061, 2020
662020
Forecasting ground vibration due to rock blasting: a hybrid intelligent approach using support vector regression and fuzzy C-means clustering
H Sheykhi, R Bagherpour, E Ghasemi, H Kalhori
Engineering with Computers 34, 357-365, 2018
452018
Predicting the Building Stone Cutting Rate Based on Rock Properties and Device Pullback Amperage in Quarries Using M5P Model Tree
SN Almasi, R Bagherpour, R Mikaeil, Y Ozcelik, H Kalhori
Geotechnical and Geological Engineering, 1-16, 2017
452017
Stability assessment of hard rock pillars using two intelligent classification techniques: A comparative study
E Ghasemi, H Kalhori, R Bagherpour
Tunnelling and Underground Space Technology 68, 32-37, 2017
442017
Experimental study on the influence of the different percentage of nanoparticles on strength and freeze–thaw durability of shotcrete
H Kalhori, B Bagherzadeh, R Bagherpour, MA Akhlaghi
Construction and Building Materials 256, 119470, 2020
362020
Application of bacteria for coal dust stabilization
M Farashahi, R Bagherpour, H Kalhori, E Ghasemi
Environmental earth sciences 78, 1-9, 2019
142019
Prediction of shotcrete compressive strength using Intelligent Methods; Neural Network and Support Vector Regression
H Kalhori, R Bagherpour
Cement-Wapno-Beton= Cement Lime Concrete 24 (2), 126-136, 2019
52019
Monitoring of drill bit wear using sound and vibration signals analysis recorded during rock drilling operations
H Kalhori, R Bagherpour, H Tudeshki
Modeling Earth Systems and Environment 10 (2), 2611-2659, 2024
22024
Wear Prediction of Rock Drill Bits Based on Geomechanical Properties of Rocks
H Kalhori, R Bagherpour, H Tudeshki
Arabian Journal for Science and Engineering, 1-14, 2023
12023
Application of soft computing methodologies to predict the 28-day compressive strength of shotcrete: a comparative study of individual and hybrid models
M Torkan, H Kalhori, MH Jalalian
Rudarsko-geološko-naftni zbornik 36 (5), 2021
12021
Laboratory tests on the strengthening of wet-mix shotcrete lining with the use of nanomaterials
H Kalhori, R Bagherpour, MA Akhlaghi, SM Mirdamadi, MN Sarvi
Rudarsko-geološko-naftni zbornik 36 (1), 2021
12021
PRIMJENA METODOLOGIJA MEKOGA RAČUNARSTVA U PREDVIĐANJU 28-DNEVNE TLAČNE ČVRSTOĆE MLAZNOGA BETONA: KOMPARATIVNA USPOREDBA INDIVIDUALNOGA I HIBRIDNOGA MODELA
M Torkan, H Kalhori, MH Jalalian
Rudarsko-geološko-naftni zbornik 36 (5), 33-48, 2021
2021
LABORATORIJSKI TEST ČVRSTOĆE MLAZNOGA BETONA DOBIVENOGA MOKRIM POSTUPKOM UPORABOM NANOMATERIJALA
H Kalhori, R Bagherpour, MA Akhlaghi, SM Mirdamadi, MN Sarvi
Rudarsko-geološko-naftni zbornik 36 (1), 49-59, 2021
2021
Prognozowanie wytrzymałości na ściskanie betonu natryskowego przy zastosowaniu inteligentnych metod obliczeniowych: sztucznej sieci neuronowej i regresji wektorów wspierających
H Kalhori, R Bagherpour
Cement Wapno Beton 22 (84, nr 2), 126--136, 2019
2019
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