Prediction of solitary wave attenuation by emergent vegetation using genetic programming and artificial neural networks

Gong, Shangpeng; Chen, Jie; Jiang, Changbo; Xu, Sudong; He, Fei; Wu, Zhiyuan

doi:10.1016/j.oceaneng.2021.109250

Cited by 19 publications

(2 citation statements)

References 23 publications

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“…This feature provides a quick overview of the most relevant interactions between the variables of the system and can help to identify new unknown links. As a result, due to its suitability for finding patterns in large datasets and handling complex modelling tasks, this empirical modelling approach is beginning to be used in more and more applications in different scientific fields, from lung cancer prediction [13] and automatic skin cancer image classification [14], to a wide range of engineering applications [15][16][17][18][19][20]. A large part of the applications is related to complex optimization problems [21][22][23] and predictive tasks in different fields [24,25].…”

Section: Methodsmentioning

confidence: 99%

A Genetic Programming Approach for Economic Forecasting with Survey Expectations

2022

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We apply a soft computing method to generate country-specific economic sentiment indicators that provide estimates of year-on-year GDP growth rates for 19 European economies. First, genetic programming is used to evolve business and consumer economic expectations to derive sentiment indicators for each country. To assess the performance of the proposed indicators, we first design a nowcasting experiment in which we recursively generate estimates of GDP at the end of each quarter, using the latest business and consumer survey data available. Second, we design a forecasting exercise in which we iteratively re-compute the sentiment indicators in each out-of-sample period. When evaluating the accuracy of the predictions obtained for different forecast horizons, we find that the evolved sentiment indicators outperform the time-series models used as a benchmark. These results show the potential of the proposed approach for prediction purposes.

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Section: Methodsmentioning

confidence: 99%

A Genetic Programming Approach for Economic Forecasting with Survey Expectations

2022

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“…Rigid vegetation represented by three types of vegetation models was tested in terms of their wave attenuation [65]. Genetic Programming (GP), Artificial Neural Networks (ANNs), and a laboratory experiment were adopted.…”

Section: Abdullah Et Al (mentioning

confidence: 99%

Mangroves As Coastal Bio-Shield: A Review of Mangroves Performance in Wave Attenuation

Kamil

Takaijudin

Hashim³

2021

Civ Eng J

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Mangroves have been recognized as soft structures that provide coastline protection. The capability of dampening waves helps minimize destruction from catastrophic events including erosive wave attacks, torrential storms, and tsunamis. Mangroves act as the first line of coastal defense in natural tragedies such as during the Super Typhoon Haiyan 2013 and Indian Ocean Tsunami 2004, whereby the leeward mangrove area encountered less damage than the unprotected area. This has further brought the attention of researchers to study the attenuation performance of these coastal vegetations. Based on an extensive literature review, this paper discusses the attenuation mechanism of mangroves, the factors influencing the dissipation performance, studies on mangrove dissipation via different approaches, the dissipation efficiency, mangrove conservation and rehabilitation efforts in Malaysia and implementation of mangrove as coastal bio-shield in other countries. The study highlights that mangrove parameters (such as species, width, density etc.) and wave parameters (such as wave period and incident wave height) are among the contributing factors in mangroves-induced wave attenuation, with different efficiency rates performed by different mangroves and waves parameters. Towards that end, several improvements are proposed for future research such as to incorporate all influencing dissipation factors with specific analysis for each species of mangroves, to perform validation on the studied mangroves attenuation capacity in different settings and circumstances, as well as to address the extent of protection by the rehabilitated mangroves. A systematic and effective management strategy incorporating ecological, forestry, and coastal engineering knowledge should be considered to ensure a sustainable mangroves ecosystem and promising coastline protection by mangroves. Doi: 10.28991/cej-2021-03091772 Full Text: PDF

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Dam break flow through rigid-emergent vegetation

Mahmoud,

Uchida

2024

Exp Fluids

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Dam failures pose a significant threat to life and property. This study investigates the potential of rigid emergent vegetation to attenuate dam break waves, reducing their destructive impact. Experiments explored the effect of varying vegetation field lengths on wave propagation. Wooden cylinders with consistent diameter (1.0 cm) and density (0.067) simulated the rigid vegetation in a straight, flat rectangular channel. Four different vegetation lengths and three bore conditions for different reservoir and tailwater depths were examined to analyze their influence on dam break wave behavior. The results demonstrate the effectiveness of vegetation in dissipating wave energy, leading to a rapid decrease in wave height and celerity. Interestingly, increasing vegetation length significantly attenuates the wave height downstream of the vegetation zone, while having no significant impact on the reflection wave height upstream of the vegetation. This finding highlights the targeted effectiveness of strategically placed vegetation in shielding downstream areas. The study also clarifies that celerity can be calculated using shallow water equations for both upstream and downstream regions with wave height and tailwater depth. However, within the vegetation, drag forces significantly reduce celerity. A novel equation, derived from wavefront profiles, was proposed and validated to accurately calculate celerity within the vegetation field. These findings provide valuable data for validating numerical models simulating dam break wave interactions with vegetation. Graphical abstract

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Prediction of solitary wave attenuation by emergent vegetation using genetic programming and artificial neural networks

Cited by 19 publications

References 23 publications

A Genetic Programming Approach for Economic Forecasting with Survey Expectations

A Genetic Programming Approach for Economic Forecasting with Survey Expectations

Mangroves As Coastal Bio-Shield: A Review of Mangroves Performance in Wave Attenuation

Dam break flow through rigid-emergent vegetation

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