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Toward Urban Water Security: Broadening the Use of Machine Learning Methods for Mitigating Urban Water Hazards
2021
Frontiers in Water
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However, the effective implementation of such an approach requires the collection and curation of large amounts of disparate data, and reliable methods for modeling processes that may be co-evolutionary ...
Due to the complex interactions of human activity and the hydrological cycle, achieving urban water security requires comprehensive planning processes that address urban water hazards using a holistic ...
The study presented a use case for a Process-Guided Deep Learning (PGDL) hybrid modeling framework for predicting depth-specific lake water temperature, which serves as an important water quality parameter ...
doi:10.3389/frwa.2020.562304
fatcat:4g4x5qsljva63fzfibqyjhsdsi
Large scale Optimal Transportation Meshfree (OTM) Simulations of Hypervelocity Impact
2013
Procedia Engineering
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The evaluation of the performance of the numerical model takes the form of a conventional validation analysis. ...
Large scale three-dimensional OTM simulations of hypervelocity impact are performed on departmental class systems using a dynamic load balancing MPI/PThreads parallel implementation of the OTM method. ...
the Predictive Modeling and Simulation of High Energy Density Dynamic Response of Materials. ...
doi:10.1016/j.proeng.2013.05.036
fatcat:npiru4z7lndctkq3vsdyscax34
Incorporating Landslide Spatial Information and Correlated Features among Conditioning Factors for Landslide Susceptibility Mapping
2021
Remote Sensing
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This study proposed a new hybrid model based on the convolutional neural network (CNN) for making effective use of historical datasets and producing a reliable landslide susceptibility map. ...
Therefore, the proposed model is capable of accurately mapping landslide susceptibility and providing a promising method for hazard mitigation and land use planning. ...
The authors also would like to thank Kun Chen from the Institute of Geophysics, China Earthquake Administration for sharing the PGA data. ...
doi:10.3390/rs13112166
fatcat:vxhukghotzhpnctlw2v3vfvuxm
Predicting Rainfall-Induced Soil Erosion Based on a Hybridization of Adaptive Differential Evolution and Support Vector Machine Classification
2021
Mathematical Problems in Engineering
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The goal of this study is to develop a machine learning model based on support vector machine (SVM) for soil erosion prediction. ...
Predicting soil erosion is a challenging task, subjecting to variation of soil characteristics, slope, vegetation cover, land management, and weather condition. ...
of this hybrid framework for tackling the problem at hand. ...
doi:10.1155/2021/6647829
fatcat:3fgnzyfcujhcnmvzwfqa6636du
Software for pest-management science: computer models and databases from the United States Department of Agriculture?Agricultural Research Service
2003
Pest Management Science
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However, rapid changes in the technology for information analysis and communication continually challenge our way of doing business. Published in ...
management simulation models. ...
Wischmeier and Smith's 'Universal Soil Loss Equation' or USLE, 6 a regression equation used for erosion prediction, based on thousands of erosion plot experiments, dates back to the 1950s and is perhaps ...
doi:10.1002/ps.682
pmid:12846319
fatcat:ynd2kr5agzd3lcly7ig6rtlnfm
ROUGH MORPHOLOGY HYBRID APPROACH FOR MAMMOGRAPHY IMAGE CLASSIFICATION AND PREDICTION
2008
International Journal of Computational Intelligence and Applications
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The objective of this research is to illustrate how rough sets can be successfully integrated with mathematical morphology and provide a more effective hybrid approach to resolve medical imaging problems ...
Then, features are extracted characterizing the underlying texture of the regions of interest by using the gray-level co-occurrence matrix. ...
These stages have been added to provide a framework for the automatic analysis of the mammogram images, which is then evaluated using a prediagnosed image database. ...
doi:10.1142/s1469026808002181
fatcat:rvy7ha7i55apffm3lsovtiv5wy
iCOASST – INTEGRATING COASTAL SEDIMENT SYSTEMS
2012
Coastal Engineering Proceedings
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The iCOASST Project will use these components to develop and apply an integrated systems modelling framework for mesoscale coastal simulation as explained in this paper. ...
However, relevant components for mesoscale coastal simulation are emerging, including: (1) new methods for system-level analysis of coast, estuary and offshore landform behaviour, which include engineering ...
System maps provide a repository for quantitative sediment budget analyses and a framework for applying predictive numerical models. ...
doi:10.9753/icce.v33.sediment.100
fatcat:2eckwrlerjbp3j7vgjx2bvzmla
Topographic outcomes predicted by stream erosion models: Sensitivity analysis and intermodel comparison
2002
Journal of Geophysical Research
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Whipple, Topographic outcomes predicted by stream erosion models: Sensitivity analysis and intermodel comparison, ...
Relief and valley density are found to vary with tectonic forcing in a manner that reflects erosion physics; these properties therefore constitute an additional set of testable predictions. ...
We thank Peter Talling for sharing data on the Enza River that appears in Table 1 and A. Allen and D. Sansom for drafting assistance. ...
doi:10.1029/2001jb000162
fatcat:gieqp3phdzcjtntkx4jljgrgby
A novel hybrid mechanistic-data-driven model identification framework using NSGA-II
2012
Journal of Hydroinformatics
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As an illustration, the framework is used for modeling wash-off and build-up of suspended solids (TSS) in highway runoff. ...
This paper describes a novel evolutionary data-driven model (DDM) identification framework using the NSGA-II multi-objective genetic algorithm. ...
engine of a hybrid model identification framework. ...
doi:10.2166/hydro.2012.026
fatcat:g55papxpwvhs5k5fwucvayain4
A Swarm Intelligence based Chaotic Morphological Approach for Software Development Cost Estimation
2018
International Journal of Intelligent Systems and Applications
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The proposed approach focuses on a mathematical morphological (MM) framework based hybrid artificial neuron (also called dilation-erosion perceptron or DEP) with algebraic foundations in complete lattice ...
The standardized process of software development was further evolved to predict the overall cost required for the development before the software is actually built. ...
For solving the SDCE problem, this model uses a combination of dilation and erosion operators from MM. ...
doi:10.5815/ijisa.2018.09.02
fatcat:kqex5m3ykzdrbgl2ki4x3hd4cy
Modeling of multilayer cohesive bank erosion with a coupled bank stability and mobile-bed model
2015
Geomorphology
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Recently, one-dimensional and two-dimensional flow and 19 mobile-bed numerical models have become useful tools for predicting morphological responses 20 to stream modifications. ...
The developed model is shown to be robust and easy to apply; it may be used 32 as a practical tool to predict bank erosion caused by fluvial and geotechnical processes. 33 Keywords: bank erosion; 2D mobile-bed ...
process-based bank stability model within a recently developed two-dimensional mobile-bed 23 model to predict bank retreat. ...
doi:10.1016/j.geomorph.2014.07.017
fatcat:5akcxnmicbffddzbd3ir2ja2sm
Machine Learning in Dam Water Research: An Overview of Applications and Approaches
2020
International Journal of Advanced Trends in Computer Science and Engineering
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For example, a preventive maintenance for replacing water assets according to the prediction from the ML model. ...
Nowadays, most water asset management systems collect and process data for data analysis and decision-making. ...
ACKNOWLEDGEMENT The authors would like to thank all the reviewers for their valuable feedback that contribute to the insights of this manuscript. ...
doi:10.30534/ijatcse/2020/56922020
fatcat:axnx7euckndk5il3lqyo3dtckq
Modeling and Simulation of Tsunami Impact: A Short Review of Recent Advances and Future Challenges
2020
Geosciences
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For reasons identified in this review, exa-scale computing efforts will impact the on-shore, highly turbulent régime to a higher degree than the 2D shallow water equations used to model tsunami propagation ...
Moreover, from the perspective of a future comprehensive multi-scale modeling infrastructure to simulate a full tsunami, we underline the current challenges associated with this approach and review the ...
Proper fine-grained modeling is important for studying erosion. ...
doi:10.3390/geosciences11010005
fatcat:k2pd33ibbrcnjkgywpzulths44
Hybrid Rockets With Nozzle In Ultra-High-Temperature Ceramic Composites
2018
Zenodo
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In the framework of the Horizon 2020 project C3HARME, an experimental campaign has been carried out to characterize a new class of Ultra-High-Temperature Ceramic Matrix Composites (UHTCMC) for near-zero ...
erosion rocket nozzles. ...
Silvio Genna (CIRTIBS Research Center) for technical support in realizing the microscopic pictures of the samples. ...
doi:10.5281/zenodo.1473368
fatcat:7dbbj6kjp5cqnb3n3c6pfzmh6a
Modeling a Two-Stage High-Power Anode Layer Thruster and its Plume
2007
Journal of Propulsion and Power
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A model of a two-stage thruster with anode layer is developed based on a two-dimensional hydrodynamic approach. ...
The erosion profiles and the total erosion rate generally agree well with available experimental data. Plasma flow analysis provides the boundary conditions for the plume expansion study. ...
The authors thank A. Yalin for providing sputtering coefficients used in these simulations and C. Marrese-Reading, A. Sengupta, M. Cappelli, and A. Semenkin for valuable discussions. ...
doi:10.2514/1.22185
fatcat:keiqitiebfbzjgsfy6ctbfk474
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