Zobrazeno 1 - 10
of 176
pro vyhledávání: '"Parveen Sihag"'
Autor:
Diksha Puri, Parveen Sihag, Mohindra Singh Thakur, Mohammed Jameel, Aaron Anil Chadee, Mohammad Azamathulla Hazi
Publikováno v:
AIMS Environmental Science, Vol 11, Iss 4, Pp 593-609 (2024)
This study is focused on the use of random forest (RF) to forecast the streamflow in the Kesinga River basin. A total of 169 data points were gathered monthly for the years 1991–2004 to create a model for streamflow prediction. The dataset was allo
Externí odkaz:
https://doaj.org/article/a693dc419f7540c38960ff3d465f014e
Estimating the effect of sand-roughened bed on hydraulic jump characteristics using heuristic models
Autor:
Rasoul Daneshfaraz, Saad Sh. Sammen, Reza Norouzi, Sani I. Abba, Ali Salem, Reza Mirzaee, Parveen Sihag, Ahmed Elbeltagi
Publikováno v:
Results in Engineering, Vol 23, Iss , Pp 102724- (2024)
The hydraulic jump occurs in open channels and downstream of hydraulic structures because these features change the flow regime from super-critical to sub-critical. To prevent downstream channel erosion and guarantee the construction of a hydraulic j
Externí odkaz:
https://doaj.org/article/d2e0d70fdd464190a8ce58c55c31d8d7
Autor:
Ahmed Y. Mohammed, Parveen Sihag
Publikováno v:
Journal of Hydroinformatics, Vol 26, Iss 3, Pp 626-640 (2024)
This study uses machine learning (ML) to predict the end-depth structure's discharge and critical depth (yc). Linear regression, M5P, random forest, random tree, reduced error pruning tree, and Gaussian process (GP) are the ML methods used in this in
Externí odkaz:
https://doaj.org/article/643b2be33fde46ceb202e498e4537532
Autor:
Diksha Puri, Raj Kumar, Parveen Sihag, Mohindra Singh Thakur, Kahkashan Perveen, Faisal M. Alfaisal, Daeho Lee
Publikováno v:
ACS Omega, Vol 8, Iss 35, Pp 31811-31825 (2023)
Externí odkaz:
https://doaj.org/article/4b4d5698811347c4ade52c27a5b80064
Publikováno v:
Journal of Hydroinformatics, Vol 25, Iss 3, Pp 1084-1102 (2023)
This paper explores the ability of multivariate adaptive regression splines, decision trees, Gaussian processes, and multiple non-linear regression equation approaches to predict the aeration efficiency at various weirs and discusses their results. I
Externí odkaz:
https://doaj.org/article/a326c7088bd04c88991c69cb228209d7
Autor:
Ahmad Alyaseen, Arunava Poddar, Navsal Kumar, Kamel Haydar, Azhar Khan, Parveen Sihag, Daeho Lee, Raj Kumar, Tej Singh
Publikováno v:
Case Studies in Construction Materials, Vol 19, Iss , Pp e02638- (2023)
Influence of Bacillus Subtilis (B. Subtilis) bacteria on the strength characteristics of 100% recycled concrete aggregate (RCA), incorporating silica fume (SF) as a substitution of cement, has been investigated in this study. Two groups of mixes (A f
Externí odkaz:
https://doaj.org/article/646be586f39941558cc7713cd36da368
Modeling of scour depth and length of a diversion channel flow system with soft computing techniques
Publikováno v:
Water Supply, Vol 23, Iss 3, Pp 1267-1283 (2023)
This study employed soft computing techniques, namely, support vector machine (SVM) and Gaussian process regression (GPR) techniques, to predict the properties of a scour hole [depth (ds) and length (Ls)] in a diversion channel flow system. The study
Externí odkaz:
https://doaj.org/article/e9ff58aba3974f919aaf184beb52390a
Autor:
Ankita Upadhya, M.S. Thakur, Parveen Sihag, Raj Kumar, Sushil Kumar, Aysha Afeeza, Asif Afzal, C Ahamed Saleel
Publikováno v:
Alexandria Engineering Journal, Vol 65, Iss , Pp 131-149 (2023)
In the present work, an attempt is made to find the most suitable prediction model for Marshall Stability and the optimistic Bitumen Content (BC) in carbon fiber reinforced asphalt concrete for flexible pavements by performing Marshall Stability test
Externí odkaz:
https://doaj.org/article/cb9949dccd14477d8763698172478c8e
Publikováno v:
Water Supply, Vol 22, Iss 10, Pp 7851-7872 (2022)
In this study, the factors affecting the formation of channel patterns and dynamics in the Givi-chay River during the period 2019–2000 were analysed. To evaluate the river strength, flaw stress and its effects on channel morphology, Landsat 7 and 8
Externí odkaz:
https://doaj.org/article/8838b02f23e1415992ee02db56bccb81
Autor:
Sachin Gowda, Vaishakh Kunjar, Aakash Gupta, Govindaswamy Kavitha, Bishnu Kant Shukla, Parveen Sihag
Publikováno v:
Urban Science, Vol 8, Iss 1, p 4 (2024)
In the realm of urban geotechnical infrastructure development, accurate estimation of the California Bearing Ratio (CBR), a key indicator of the strength of unbound granular material and subgrade soil, is paramount for pavement design. Traditional la
Externí odkaz:
https://doaj.org/article/9be5b0b105394199b87498ea84122ab9