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A Comparative Study of Extreme Learning Machines and Support Vector Machines in Prediction of Sediment Transport in Open Channels

2016 International Journal of Engineering  
The limiting velocity in open channels to prevent long-term sedimentation is predicted in this paper using a powerful soft computing technique known as Extreme Learning Machines (ELM).  ...  The comparison of the ELM and SVM methods indicates a good performance for both methods in the prediction of Fr.  ...  In this study the ELM approach is developed to predict sediment transport in open channels.  ... 
doi:10.5829/idosi.ije.2016.29.11b.03 fatcat:jturvp6ckfb3ph6742r5ry6y44

Remote Sensing of Sediment Discharge in Rivers Using Sentinel-2 Images and Machine-Learning Algorithms

Ahmed Mohsen, Ferenc Kovács, Tímea Kiss
2022 Hydrology  
The at-a-station hydraulic geometry (AHG) power–law method was compared to the at-many-stations hydraulic geometry (AMHG) method; in addition, a novel AHG machine-learning (ML) method was introduced to  ...  The surface reflectance of Sentinel-2 images was correlated to in situ suspended sediment concentration (SSC) by support vector machine (SVM), random forest (RF), artificial neural network (ANN), and combined  ...  Acknowledgments: The authors would like to thank the Lower Tisza Hydrological Directorate (ATIVIZIG) for providing the hydrological data.  ... 
doi:10.3390/hydrology9050088 fatcat:ukgkmbxq2feuja5hnidfkxo4ay

Application of Machine Learning Model for the Prediction of Settling Velocity of Fine Sediments

Wing Son Loh, Ren Jie Chin, Lloyd Ling, Sai Hin Lai, Eugene Zhen Xiang Soo
2021 Mathematics  
Hence, the machine learning model appears as a suitable tool to predict the settling velocity of fine sediments in water bodies.  ...  In this study, three different machine learning-based models, namely, the radial basis function neural network (RBFNN), back propagation neural network (BPNN), and self-organizing feature map (SOFM), were  ...  Nevertheless, the successful results have also opened doors for other types of applications not limited to sedimentation studies, such as the transport  ... 
doi:10.3390/math9233141 fatcat:bx5qdesh3rdrzo5fl4g6gep3pm

Impacts of Urban Floods on Road Connectivity - A Review and Systematic Bibliometric Analysis

Ashok Kadaverugu, Kasi Viswanadh Gorthi, Nageshwar Rao Chintala
2021 Current World Environment  
We observed a gap in harmonized data availability, due to the unstructured data formats at several scales, which hinders a generalized approach for flood risk modeling studies for urban planning.  ...  Urban floods are paralyzing surface transportation and inflicting heavy economic losses.  ...  Funding The research did not receive any specific grant from funding agencies in the public, commercial or notfor-profit sectors.  ... 
doi:10.12944/cwe.16.2.22 fatcat:axrfidtkyjfcrpzov5522btfhq

Advanced methods to investigate hydro‐morphological processes in open‐water environments

Stefan Haun, Stephan Dietrich
2021 Earth Surface Processes and Landforms  
Hydro-morphology describes the interactions between water and sediments in fluvial systems and the corresponding processes across all spatial and temporal scales.  ...  Finally, a brief look into the future reveals the use of artificial intelligence (AI) machine learning, for example based on artificial neural networks (ANN), in hydro-environmental research (Demirci  ...  A major challenge with this approach is the acquisition of suitable training data appropriate for machine learning models that can predict land-cover type information from image radiance values.  ... 
doi:10.1002/esp.5131 fatcat:zmpuczvuujg4pijkgtpbvct6jm

Machine-learning approach to holographic particle characterization

Aaron Yevick, Mark Hannel, David G. Grier
2014 Optics Express  
Here, we demonstrate that machine-learning techniques based on support vector machines (SVMs) can analyze holographic video microscopy data in real time on low-power computers.  ...  Our SVMs are implemented with scikit-learn, an open-source machine learning software package [15] that builds upon the libsvm library of Support Vector Machine algorithms [16, 17] .  ...  Other machine-learning techniques also might be effective for analyzing holograms of colloidal particles.  ... 
doi:10.1364/oe.22.026884 pmid:25401836 fatcat:rluklmfepnbwlifqwtppjaucra

Sessions

2021 2021 Moratuwa Engineering Research Conference (MERCon)  
Lability and Bioavailability of Toxic Heavy Metals in Ratnapura District Gem Sediments, Sri Lanka T3-4: Big Data, Machine Learning, and Cloud Computing 1 11:00 Fine-Tuning Self-Supervised Multilingual  ...  Capabilities 11:30 The Readiness of Teachers in Adopting Flipped Classrooms and Open Educational Resources in Undergraduate Blended Learning 11:45 A Conceptual Framework for the Identification  ... 
doi:10.1109/mercon52712.2021.9525726 fatcat:epb7jkwdv5fvhcs5h5rwwcspae

Open Channel Sluice Gate Scouring Parameters Prediction: Different Scenarios of Dimensional and Non-Dimensional Input Parameters

Ali Yousif, Sadeq Sulaiman, Lamine Diop, Mohammad Ehteram, Shamsuddin Shahid, Nadhir Al-Ansari, Zaher Yaseen
2019 Water  
The applicability of modern data-intelligence technique known as extreme learning machine (ELM) to simulate scour characteristics has been examined in this study.  ...  The determination of scour characteristics in the downstream of sluice gate is highly important for designing and protection of hydraulic structure.  ...  Figure 3 . 3 The structure of the extreme learning machine model used in the present study. Figure 3 . 3 The structure of the extreme learning machine model used in the present study.  ... 
doi:10.3390/w11020353 fatcat:jqczkurcuzberotdslp5rxdr4q

Modeling water quality in watersheds: From here to the next generation

B. Fu, J. S. Horsburgh, A. J. Jakeman, C. Gualtieri, T. Arnold, L. Marshall, T. R. Green, N. W. T. Quinn, M. Volk, R. J. Hunt, L. Vezzaro, B. F. W. Croke (+3 others)
2020 Water Resources Research  
In this synthesis, we assess present research and anticipate future development needs in modeling water quality in watersheds.  ...  Finally, we make three recommendations to provide a path forward for improving watershed water quality modeling science, infrastructure, and practices.  ...  Opportunities for hybrids of machine learning and process-based modeling deserve further exploration, particularly to identify deviations in behavior of machine learning and process model simulated results  ... 
doi:10.1029/2020wr027721 pmid:33627891 pmcid:PMC7898158 fatcat:pxnzrmgr7vadfbmipaxpzxtzwa

Derivation of Sediment Transport Models for Sand Bed Rivers from Data-Driven Techniques [chapter]

Vasileios Kitsikoudis, Epaminondas Sidiropoulos, Vlassios Hrissanthou
2013 Sediment Transport Processes and Their Modelling Applications  
The determination of the input parameters was accomplished by a tentative assessment of some of the widely used dimensionless parameters in sediment transport and open channel hydraulics.  ...  The rate of energy per unit weight of water, available for transporting water and sediment in an open channel with reach length x and total drop of Y, is dY dx dY VS dt dt dx = = (12) Sediment Transport  ...  Appendix B For the calculation of particle fall velocity in a clear, still fluid, van Rijn (1984) suggested the use of the Stokes law for sediment particles smaller than 0.1 mm For suspended sand particles  ... 
doi:10.5772/53432 fatcat:rbhbgzojvnfihputplowirpeje

Paleohydrology and Machine-Assisted Estimation of Paleogeomorphology of Fluvial Channels of the Lower Middle Pennsylvanian Allegheny Formation, Birch River, WV

Oluwasegun Abatan, Amy Weislogel
2020 Frontiers in Earth Science  
In order to enhance paleohydrological estimates, machine learning methods including multiple regression and support vector regression (SVR) algorithms were used to improve the dune height, and channel  ...  Rivers transport sediments in a source to sink system while responding to allogenic controls of the depositional system.  ...  AUTHOR CONTRIBUTIONS All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.  ... 
doi:10.3389/feart.2019.00361 fatcat:lgfft52m6bdkbksfq5nlwhm7hq

Soft Sensing of Non-Newtonian Fluid Flow in Open Venturi Channel Using an Array of Ultrasonic Level Sensors—AI Models and Their Validations

Khim Chhantyal, Håkon Viumdal, Saba Mylvaganam
2017 Sensors  
In oil and gas and geothermal installations, open channels followed by sieves for removal of drill cuttings, are used to monitor the quality and quantity of the drilling fluids.  ...  Fuzzy logic, neural networks and support vector regression algorithms applied to the data from temporal and spatial ultrasonic level measurements of the drilling fluid in the open channel give estimates  ...  We acknowledge the collaboration with and support from STATOILfor providing and commissioning the open channel Venturi rig with various types of sensors and control systems dedicated to flow studies of  ... 
doi:10.3390/s17112458 pmid:29072595 pmcid:PMC5713661 fatcat:qsohrworufff7pofpqee4nvzxe

The future of coastal and estuarine modeling: Findings from a workshop

Oliver B. Fringer, Clint N. Dawson, Ruoying He, David K. Ralston, Y. Joseph Zhang
2019 Ocean Modelling  
Other topics that require significantly more work to better parameterize include nearshore wave modeling, sediment transport modeling, and morphodynamics.  ...  Subjectivity can also be reduced through more engagement with the applied mathematics and computer science communities to develop methods for robust parameter estimation and uncertainty quantification.  ...  Acknowledgments We thank Carmen Torres at Stanford University and Jennifer Warrillow at North Carolina State University for their assistance with workshop logistics.  ... 
doi:10.1016/j.ocemod.2019.101458 fatcat:636yn253uzf65gipg7uoknofl4

Monsoon: Past, Present and Future

P. Maharana, A. P. Dimri
2018 Proceedings of the Indian National Science Academy  
In the recent past, with the availability of enormous datasets and advanced computational skills, hydrological science is trending towards integration of multidimensional studies for the comprehension  ...  Numerous studies have been carried out in varied hydrological, climatic and geological settings of India during the last decade.  ...  Acknowledgement Authors thank the Director, CSIR-NGRI for permission to publish this paper. We greatly appreciate Prof. Harsh K. Gupta for inviting us to write this article.  ... 
doi:10.16943/ptinsa/2018/49513 fatcat:4g5zrszcdrf4pl2j4k6qoxv2yq

Suspended Sediment Concentration Estimation from Landsat Imagery along the Lower Missouri and Middle Mississippi Rivers Using an Extreme Learning Machine

Kyle Peterson, Vasit Sagan, Paheding Sidike, Amanda Cox, Megan Martinez
2018 Remote Sensing  
learning machine (ELM).  ...  This study demonstrates the benefit of ELM over traditional modeling methods for the prediction of SSC based on satellite data and its potential to improve sediment transport and monitoring along large  ...  The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.  ... 
doi:10.3390/rs10101503 fatcat:qh6unmvzgva3jej75y7ivr6w2q
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