Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Seyed Babak Haji Seyed Asadollah"'
Publikováno v:
Ain Shams Engineering Journal, Vol 12, Iss 4, Pp 3521-3530 (2021)
In the current research, a newly developed ensemble intelligent predictive model called Bagging Regression (BGR) is proposed to predict the compressive strength of a hollow concrete masonry prism (fp). A matrix of input combinations is constructed ba
Externí odkaz:
https://doaj.org/article/64843f78f4834b028aad1ee593b10856
Autor:
Sangeeta, Seyed Babak Haji Seyed Asadollah, Ahmad Sharafati, Parveen Sihag, Nadhir Al-Ansari, Kwok-Wing Chau
Publikováno v:
Engineering Applications of Computational Fluid Mechanics, Vol 15, Iss 1, Pp 889-901 (2021)
This study compares several advanced machine learning models to obtain the most accurate method for predicting the aeration efficiency (E20) through the Parshall flume. The required dataset is obtained from the laboratory tests using different flumes
Externí odkaz:
https://doaj.org/article/ef60f06b16674847b4ac2ce3c05c957a
Autor:
Ahmad Sharafati, Masoud Haghbin, Seyed Babak Haji Seyed Asadollah, Nand Kumar Tiwari, Nadhir Al-Ansari, Zaher Mundher Yaseen
Publikováno v:
Applied Sciences, Vol 10, Iss 11, p 3714 (2020)
Considering the scouring depth downstream of weirs is a challenging issue due to its effect on weir stability. The adaptive neuro-fuzzy inference systems (ANFIS) model integrated with optimization methods namely cultural algorithm, biogeography based
Externí odkaz:
https://doaj.org/article/4d3d821d518d4049a1fe55e6fa14a2a3
Publikováno v:
Theoretical and Applied Climatology. 150:453-467
Autor:
Najeebullah Khan, Ahmad Sharafati, Xiaojun Wang, Shamsuddin Shahid, Seyed Babak Haji Seyed Asadollah, Eun-Sung Chung
Publikováno v:
Stochastic Environmental Research and Risk Assessment. 36:1959-1974
Climate change has caused a rise in temperature extremes, particularly heatwaves, in recent decades. Physical-empirical models are developed in this study using two classical machine learning algorithms, namely decision tree (DT) and random forests,
Publikováno v:
Environmental science and pollution research international.
Sediment pick-up rate has been investigated using experimental and numerical approaches. However, the use of soft computing methods for its prediction has received less attention so far. In this study, genetic programming (GP), grammatical evolution
Publikováno v:
Theoretical and Applied Climatology. 145:473-487
This study represents a new strategy for assessing how climate change has impacted urban water demand per capita in Neyshabur, Iran. Future rainfall depths and temperature variations are projected using several general circulation models (GCMs) for t
Publikováno v:
Environmental Monitoring and Assessment. 194
Logical management and decision-making on water resources require reliable weather variables, where precipitation is considered the main weather variable. Accurate estimation of precipitation is the most important topic in hydrological studies. Due t
Publikováno v:
Process Safety and Environmental Protection. 140:68-78
Accurate simulation of wastewater effluent parameters is a vital concern to reduce the operational costs of a wastewater treatment plant. In this way, a reliable predictive model is a necessity to achieve an acceptable performance. This study represe
Publikováno v:
Hydrological Sciences Journal. 65:2022-2042
Ensemble machine learning models have been widely used in hydro-systems modeling as robust prediction tools that combine multiple decision trees. In this study, three newly developed ensemble machine learning models, namely gradient boost regression