Using an Improved Ant Lion Optimizer Algorithm and Wireless Network to Explore Nondestructive Testing Technology for Water Conservancy Engineering

Shang, Hui

doi:10.1109/jsen.2021.3062571

Cited by 6 publications

(4 citation statements)

References 16 publications

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“…The ALO algorithm, first introduced in 2015 by Mirjalili (2015), simulates the predatory behavior of the ant lion insect species during the larval stage (Shang, 2021). In the ALO algorithm, the positions of prey and ant lions are determined randomly in the search space.…”

Section: Modeling Methodologymentioning

confidence: 99%

“…When prey appears, the ant lion will throw sand toward the edge of the hole to slide the prey towards the lion ant. The hunting process ends with reconstructing the hole in the sand and identifying the elite ant lion (Shang, 2021). The performance of the ALO algorithm depends on the following assumptions: The prey moves randomly in the search space, and the traps of the ant lion affect the movement of the prey. The size of the hole in the sand and the hunting ability of the ant lion is proportional to its fitness. The predation process is repeated in each loop (Moayedi et al, 2019).…”

Section: Modeling Methodologymentioning

confidence: 99%

Section: Ant Lion Optimizermentioning

confidence: 99%

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Flood susceptibility assessment using hybrid machine learning and remote sensing in Quang Tri province, Vietnam

Nguyen

2022

Transactions in GIS

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Flooding is the most dangerous of all environmental hazards and leads to significant impacts both on the environment and on human life. Environmental protection and water management can be achieved by modeling flood susceptibility, to inform strategy that will reduce flood damage. The aim of this study is to develop novel hybrid models based on a radial basis functions neural network (RBFNN), arithmetic optimization algorithm (AOA), artificial bee colony (ABC), and ant lion optimizer (ALO), to build flood susceptibility maps in the Quang Tri province of Vietnam. The obtained models were trained and validated using 1511 flood points and 14 conditioning factors. Various statistical indices were used to assess the performance of the models, namely root mean square error, receiver operation characteristics (ROC), area under the receiver operating characteristic curve (AUC), and the coefficient of determination (R2). The comparison analysis highlights that the RBFNN‐ABC model was better than other models with an AUC of 0.98, followed by RBFNN‐AOA, support vector machine, and random forest, all with an AUC value of 0.96, and finally RBFNN‐ALO, with an AUC of 0.95. From the flood susceptibility map, it can be seen that the eastern areas of the study area have high and very high flood susceptibility, that requires local government attention. The approach and results of this study can support national and local authorities, decision‐makers, and other planners in the construction of appropriate strategies to reduce potential damage in the future.

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Section: Modeling Methodologymentioning

confidence: 99%

Section: Modeling Methodologymentioning

confidence: 99%

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Flood susceptibility assessment using hybrid machine learning and remote sensing in Quang Tri province, Vietnam

Nguyen

2022

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“…With the progress of science and technology, hydraulics has undergone great changes [1,2]. Modern hydraulics is developed on the basis of the combination of classical hydraulics and hydrodynamics, and on the basis of computing technology and new testing technology.…”

Section: Introductionmentioning

confidence: 99%

Hydrodynamic Model of Hydraulic Engineering Based on Trigonometric Function Relation Equation

Liu

Jian

2023

Applied Mathematics and Nonlinear Sciences

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In order to explore the application of fluid mechanics technology in water conservancy and hydropower stations, the author proposes the study of hydraulic engineering fluid mechanics model based on trigonometric function relationship equation. According to standard k- ε Double equation and Reynolds time average (N-S) equation, given the runner boundary conditions, establish the mathematical model of the internal flow of the hydraulic turbine. Through CFD simulation technology, the runner of hydraulic turbine is numerically simulated to obtain the velocity distribution and blade pressure distribution inside the runner, movable guide vane and fixed guide vane, the reliability of the design is improved, and the application of CFD technology in hydropower project is analyzed with an example. The results show that, when the diameter of guide vane distribution circle is 4760mm, the scheme is optimal, and the relative efficiency under the optimal working condition is 96.35%. The flow of the modified runner from the inlet of the volute to the outlet of the draft tube is very stable under the optimal working condition, and there is no obvious vortex, especially there is no obvious vortex belt and vortex at the outlet of the runner; There is no obvious vortex in the draft tube, the flow on both sides of the pier is very uniform, and the flow on one side is not significantly greater than that on the other side, which fully shows that the flow performance of the modified runner is good. After reconstruction, the runner outlet flow field is good, and the internal flow line of the draft tube is smooth. The application prospect of hydrodynamic algorithm for hydraulic engineering is relatively broad.

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Energy Aware Optimal Virtual Machine Scheduling in Cloud Environment Using Hybridized Egret Swarm with Sea Lion Optimization Algorithm

Vhatkar,

Kathole,

Lonare

et al. 2024

Neural Process Lett

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Using an Improved Ant Lion Optimizer Algorithm and Wireless Network to Explore Nondestructive Testing Technology for Water Conservancy Engineering

Cited by 6 publications

References 16 publications

Flood susceptibility assessment using hybrid machine learning and remote sensing in Quang Tri province, Vietnam

Flood susceptibility assessment using hybrid machine learning and remote sensing in Quang Tri province, Vietnam

Hydrodynamic Model of Hydraulic Engineering Based on Trigonometric Function Relation Equation

Energy Aware Optimal Virtual Machine Scheduling in Cloud Environment Using Hybridized Egret Swarm with Sea Lion Optimization Algorithm

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