Simulation of time-series groundwater parameters using a hybrid metaheuristic neuro-fuzzy model
A Azizpour, MA Izadbakhsh, S Shabanlou… - … Science and Pollution …, 2022 - Springer
The estimation of qualitative and quantitative groundwater parameters is an essential task.
In this regard, artificial intelligence (AI) techniques are extensively utilized as accurate …
In this regard, artificial intelligence (AI) techniques are extensively utilized as accurate …
Estimation of water level fluctuations in groundwater through a hybrid learning machine
A Azizpour, MA Izadbakhsh, S Shabanlou… - Groundwater for …, 2021 - Elsevier
In the present study, a new hybrid artificial intelligence-based model is presented to simulate
monthly time-series data relevant to groundwater quantity collected from an observation well …
monthly time-series data relevant to groundwater quantity collected from an observation well …
Sensitivity analysis of parameters influencing the ice–seabed interaction in sand by using extreme learning machine
Ice gouging problem is a significant challenge threatening the integrity of subsea pipelines
in the Arctic (eg, Beaufort Sea) and even non-Arctic (eg, Caspian Sea) offshore regions …
in the Arctic (eg, Beaufort Sea) and even non-Arctic (eg, Caspian Sea) offshore regions …
[HTML][HTML] Iceberg-seabed interaction evaluation in clay seabed using tree-based machine learning algorithms
In Arctic offshore regions, the oil and gas hydrocarbons are transferred to the onshore
basins through the subsea pipelines. However, the operational integrity of the subsea …
basins through the subsea pipelines. However, the operational integrity of the subsea …
[HTML][HTML] Iceberg-seabed interaction analysis in sand by a random forest algorithm
Iceberg-seabed interaction that threatens subsea pipelines and structures is a challenging
and costly engineering design aspect of Arctic offshore infrastructures. In this study, the sub …
and costly engineering design aspect of Arctic offshore infrastructures. In this study, the sub …
Evaluation of discharge coefficient of triangular side orifices by using regularized extreme learning machine
RG Moghadam, B Yaghoubi, A Rajabi… - Applied Water …, 2022 - Springer
The present paper attempts to reproduce the discharge coefficient (DC) of triangular side
orifices by a new training approach entitled “Regularized Extreme Learning Machine …
orifices by a new training approach entitled “Regularized Extreme Learning Machine …
Ice-seabed interaction modeling in clay by using evolutionary design of generalized group method of data handling
Ice-induced scour is a serious challenge for the subsea pipelines in the Arctic shallow
waters. Estimation of the maximum pipeline deformation and its minimum burial depth can …
waters. Estimation of the maximum pipeline deformation and its minimum burial depth can …
A wavelet-outlier robust extreme learning machine for rainfall forecasting in Ardabil City, Iran
In this paper, the monthly long-term precipitation of the city of Ardabil from 1976 to 2020 is
simulated by a modern hybrid learning machine. To this end, the Wavelet and Outlier Robust …
simulated by a modern hybrid learning machine. To this end, the Wavelet and Outlier Robust …
Evaluation of ice-seabed interaction mechanism in sand by using self-adaptive evolutionary extreme learning machine
Recent discovered oil and gases in the Arctic area have heightened the need for more
attention to ice-seabed interaction during an ice scouring event. The seabed is gouged by …
attention to ice-seabed interaction during an ice scouring event. The seabed is gouged by …
[HTML][HTML] A non-tuned machine learning method to simulate ice-seabed interaction process in clay
Exploitation of oil and gas in the Arctic area is expected to expand in the coming years.
These hydrocarbons are transferred through subsea pipelines from offshore to onshore; …
These hydrocarbons are transferred through subsea pipelines from offshore to onshore; …