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Parveen Sihag
Parveen Sihag
Ph.D
在 nitkkr.ac.in 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Modelling of impact of water quality on infiltration rate of soil by random forest regression
B Singh, P Sihag, K Singh
Modeling Earth Systems and Environment 3, 999-1004, 2017
2102017
Prediction of unsaturated hydraulic conductivity using adaptive neuro-fuzzy inference system (ANFIS)
P Sihag, NK Tiwari, S Ranjan
ISH Journal of Hydraulic Engineering 25 (2), 132-142, 2019
1102019
Estimation and inter-comparison of infiltration models
P Sihag, NK Tiwari, S Ranjan
Water Science 31 (1), 34-43, 2017
1092017
Soft computing techniques: systematic multiscale models to predict the compressive strength of HVFA concrete based on mix proportions and curing times
A Mohammed, S Rafiq, P Sihag, R Kurda, W Mahmood
Journal of Building Engineering 33, 101851, 2021
1032021
Modelling of infiltration of sandy soil using gaussian process regression
P Sihag, NK Tiwari, S Ranjan
Modeling Earth Systems and Environment 3, 1091-1100, 2017
1032017
Modelling of impact of water quality on recharging rate of storm water filter system using various kernel function based regression
P Sihag, P Jain, M Kumar
Modeling earth systems and environment 4, 61-68, 2018
1022018
Support vector regression (SVR) and grey wolf optimization (GWO) to predict the compressive strength of GGBFS-based geopolymer concrete
HU Ahmed, RR Mostafa, A Mohammed, P Sihag, A Qadir
Neural Computing and Applications 35 (3), 2909-2926, 2023
922023
ANN, M5P-tree and nonlinear regression approaches with statistical evaluations to predict the compressive strength of cement-based mortar modified with fly ash
A Mohammed, S Rafiq, P Sihag, R Kurda, W Mahmood, K Ghafor, ...
Journal of Materials Research and Technology 9 (6), 12416-12427, 2020
872020
Modeling the infiltration process with soft computing techniques
P Sihag, B Singh, A Sepah Vand, V Mehdipour
ISH Journal of Hydraulic Engineering 26 (2), 138-152, 2020
742020
Comparative evaluation of infiltration models
AS Vand, P Sihag, B Singh, M Zand
KSCE Journal of Civil Engineering 22, 4173-4184, 2018
732018
Metamodel techniques to estimate the compressive strength of UHPFRC using various mix proportions and a high range of curing temperatures
W Emad, AS Mohammed, A Bras, PG Asteris, R Kurda, Z Muhammed, ...
Construction and Building Materials 349, 128737, 2022
692022
Wave height predictions in complex sea flows through soft-computing models: Case study of Persian Gulf
T Sadeghifar, GFC Lama, P Sihag, A Bayram, O Kisi
Ocean Engineering 245, 110467, 2022
662022
Comparing different methods for statistical modeling of particulate matter in Tehran, Iran
V Mehdipour, DS Stevenson, M Memarianfard, P Sihag
Air Quality, Atmosphere & Health 11, 1155-1165, 2018
642018
Prediction of unsaturated hydraulic conductivity using fuzzy logic and artificial neural network
P Sihag
Modeling Earth Systems and Environment 4, 189-198, 2018
642018
Support vector regression-based modeling of cumulative infiltration of sandy soil
P Sihag, NK Tiwari, S Ranjan
ISH journal of hydraulic engineering 26 (1), 44-50, 2020
622020
Predicting bond strength of FRP bars in concrete using soft computing techniques
MS Thakur, SM Pandhiani, V Kashyap, A Upadhya, P Sihag
Arabian Journal for Science and Engineering 46, 4951-4969, 2021
602021
Random forest, M5P and regression analysis to estimate the field unsaturated hydraulic conductivity
P Sihag, S Mohsenzadeh Karimi, A Angelaki
Applied Water Science 9 (5), 129, 2019
602019
Application of SVM, ANN, GRNN, RF, GP and RT models for predicting discharge coefficients of oblique sluice gates using experimental data
F Salmasi, M Nouri, P Sihag, J Abraham
Water Supply 21 (1), 232-248, 2021
572021
Estimation of models for cumulative infiltration of soil using machine learning methods
A Angelaki, S Singh Nain, V Singh, P Sihag
ISH Journal of Hydraulic Engineering 27 (2), 162-169, 2021
522021
Assessment of soft computing techniques for the prediction of compressive strength of bacterial concrete
F Almohammed, P Sihag, SS Sammen, KA Ostrowski, K Singh, ...
Materials 15 (2), 489, 2022
502022
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