Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development | Paper Citation Record

Observation 7c7865c4-c7e9-4b03-a3fa-b0e829af742f · outbound

This paper cites A high-resolution godunov-type scheme in finite volumes for the 2d shallow-water equations.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development A high-resolution godunov-type scheme in finite volumes for the 2d shallow-water equations

Reference 1

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Observation a2cfc14d-c34b-4cda-b570-1a73a58651d6 · outbound

This paper cites R., Natalizio, E., Calafate, C.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development R., Natalizio, E., Calafate, C

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.833322Z

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Observation 000ac99b-b486-441a-ad00-1ccd361c5bf7 · outbound

This paper cites Solution of the 2d shallow water equations using the finite volume method on unstructured triangular meshes.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Solution of the 2d shallow water equations using the finite volume method on unstructured triangular meshes

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.813522Z

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Observation d2daa47a-5f5f-4636-b58a-8c18f8447652 · outbound

This paper cites t., 2004.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development t., 2004

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.792178Z

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Observation 3ffb411b-53ea-4b99-a233-bc5720581109 · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 5

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Observation 0747611e-8442-4783-8983-affd90da127b · outbound

This paper cites A., Ravela, S., Rus, D., 2008.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development A., Ravela, S., Rus, D., 2008

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.773238Z

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Observation c10a3646-2fc8-4678-9d86-59c20251fec2 · outbound

This paper cites A hybrid method for flood simulation in small catchments combining hydrodynamic and hydrological techniques.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development A hybrid method for flood simulation in small catchments combining hydrodynamic and hydrological techniques

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.753254Z

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Observation 83fccf35-2d28-46ff-b34d-2a0edd57ca8a · outbound

This paper cites Recursive bayesian estimation: Navigation and tracking applications.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Recursive bayesian estimation: Navigation and tracking applications

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.734654Z

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Observation fdd05a91-9190-4a88-9505-18c7a9a36077 · outbound

This paper cites Flood disasters: lessons from the past—worries for the future.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Flood disasters: lessons from the past—worries for the future

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.716839Z

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Observation fbbe5f90-96a9-4bd0-b801-339c4da3c2d2 · outbound

This paper cites A well-balanced reconstruction of wet/dry fronts for the shallow water equations.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development A well-balanced reconstruction of wet/dry fronts for the shallow water equations

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.698202Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a312669a-d463-4929-b4c9-a1cca11d3102 · outbound

This paper cites The validity of flow approximations when simulating catchment-integrated flash floods.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development The validity of flow approximations when simulating catchment-integrated flash floods

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.681448Z

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Observation 0e3cd864-e613-455a-bf18-74eec9239a5c · outbound

This paper cites R., S tra, M.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development R., S tra, M

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.662474Z

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Observation 73b999ac-a509-4b6f-9761-9ecae452931c · outbound

This paper cites Data-driven synthesis of smoke flows with cnn-based feature descriptors.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Data-driven synthesis of smoke flows with cnn-based feature descriptors

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.644719Z

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Observation 4f8aa9ad-0eb4-440d-a3b9-98b49390cf97 · outbound

This paper cites Daily reservoir inflow forecasting using artificial neural networks with stopped training approach.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Daily reservoir inflow forecasting using artificial neural networks with stopped training approach

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.627319Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3f345a5a-ba7f-4011-ab1f-ce0d0cbfe85c · outbound

This paper cites \"U ber die partiellen differenzengleichungen der mathematischen physik.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development \"U ber die partiellen differenzengleichungen der mathematischen physik

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.607833Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4610ee5e-c524-4883-91f0-fc57207594f0 · outbound

This paper cites Flood prediction using time series data mining.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Flood prediction using time series data mining

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.590965Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fdd90c88-dc11-401e-acd1-4b8fbcd1315b · outbound

This paper cites Generating images with perceptual similarity metrics based on deep networks.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Generating images with perceptual similarity metrics based on deep networks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.574069Z

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Observation 6c2d8ad5-ec04-4cec-98d7-4273b0b4ae7a · outbound

This paper cites Robots for environmental monitoring: Significant advancements and applications.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Robots for environmental monitoring: Significant advancements and applications

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.555964Z

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Observation c07d117f-15e5-4c96-9933-5558acf7cb33 · outbound

This paper cites H., 2014.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development H., 2014

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.538293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation aa130f65-b8ac-4929-bd74-2f83e2618aa0 · outbound

This paper cites Flooding, vulnerability and coping strategies: local responses to a global threat.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Flooding, vulnerability and coping strategies: local responses to a global threat

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.519710Z

Source-reported events for the cited work

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Observation cd4e48bb-566b-4975-a224-77f0e289ed54 · outbound

This paper cites P., 1986.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development P., 1986

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.501377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5f6bf9f1-f615-495d-b599-cb5072f32839 · outbound

This paper cites Scaling and similarity in rough channel flows.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Scaling and similarity in rough channel flows

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.483653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cba83b5e-225e-4e54-b433-06757727e7e9 · outbound

This paper cites Generative adversarial nets.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Generative adversarial nets

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.465255Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1cc05b8a-8213-4e65-945b-b8fefa94e59f · outbound

This paper cites Deep residual learning for image recognition.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Deep residual learning for image recognition

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.446886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3fb80aab-ffb4-4ea4-b5a4-44b1c966141f · outbound

This paper cites A., Konev, A., Bl \"o schl, G., 2015.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development A., Konev, A., Bl \"o schl, G., 2015

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.429455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a6cf1da1-159f-47ee-8b41-5d8dce22b0de · outbound

This paper cites B., Gibbs, M.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development B., Gibbs, M

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.411240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9d31bcea-432b-40bc-87d8-5f5299cc70c7 · outbound

This paper cites E., 1960.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development E., 1960

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.394115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5586da38-f994-4a3d-8134-963932b007f1 · outbound

This paper cites The data-driven approach as an operational real-time flood forecasting model.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development The data-driven approach as an operational real-time flood forecasting model

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.376821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 07a3cdba-541a-4d0b-b395-6e20f2f28371 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Adam: A Method for Stochastic Optimization

Reference 29

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Observation 60cd9e89-7ab8-4a07-8608-2fa7043e7ec1 · outbound

This paper cites V., Shirshov, G., Melnikova, N., Belleman, R.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development V., Shirshov, G., Melnikova, N., Belleman, R

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.357952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e455ae23-d07d-4cdd-99f6-e8499ce469e1 · outbound

This paper cites Central-upwind schemes for the saint-venant system.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Central-upwind schemes for the saint-venant system

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.339834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cb79f252-37fa-4e88-b8c9-09a85cb0fcac · outbound

This paper cites Semidiscrete central-upwind schemes for hyperbolic conservation laws and hamilton--jacobi equations.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Semidiscrete central-upwind schemes for hyperbolic conservation laws and hamilton--jacobi equations

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.321492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 68effa41-01ef-43ba-a265-1ab1474368ec · outbound

This paper cites A second-order well-balanced positivity preserving central-upwind scheme for the saint-venant system.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development A second-order well-balanced positivity preserving central-upwind scheme for the saint-venant system

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.302918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 07df5725-011e-41aa-8be4-3b5d0c9994eb · outbound

This paper cites A comparison of nonlinear flood forecasting methods.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development A comparison of nonlinear flood forecasting methods

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.281976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 22d3c9ba-1810-4705-827b-398dfdbe4847 · outbound

This paper cites Deep learning.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Deep learning

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.262855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 91989d1d-d930-4d7c-aff1-adea5c7a1ade · outbound

This paper cites Gradient-based learning applied to document recognition.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Gradient-based learning applied to document recognition

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.243210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f639c138-e29b-4099-a0c4-be61b6ae7f34 · outbound

This paper cites Combining markov random fields and convolutional neural networks for image synthesis.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Combining markov random fields and convolutional neural networks for image synthesis

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.223238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 96d179a0-5e4f-4367-a80b-91f303db88aa · outbound

This paper cites Numerical resolution of well-balanced shallow water equations with complex source terms.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Numerical resolution of well-balanced shallow water equations with complex source terms

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.203248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bd911b72-b312-4acf-8e30-ad27c687baa2 · outbound

This paper cites Some methods for classification and analysis of multivariate observations.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Some methods for classification and analysis of multivariate observations

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.185221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c91215d4-2364-4039-b573-40e002bd4eb3 · outbound

This paper cites Conditional Generative Adversarial Nets.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Conditional Generative Adversarial Nets

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-14T11:26:49.447769Z

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Observation 438576d8-23c7-430c-95d7-d0ebab738de9 · outbound

This paper cites Uavs for smart cities: Opportunities and challenges.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Uavs for smart cities: Opportunities and challenges

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.165646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 583d4e7a-4839-4b72-9bbb-7bcb782c25bd · outbound

This paper cites E., Gruntfest, E., 2002.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development E., Gruntfest, E., 2002

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.147127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a5b870f5-7f74-4413-a9a7-9a87575f6885 · outbound

This paper cites RFFS and HYRAD: Integrated systems for rainfall and river flow forecasting in real-time and their application in Yorkshire.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development RFFS and HYRAD: Integrated systems for rainfall and river flow forecasting in real-time and their application in Yorkshire

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.128471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ad508fd9-ec26-4e8e-8346-b64b2cd9e4a2 · outbound

This paper cites Flood prediction using machine learning models: Literature review.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Flood prediction using machine learning models: Literature review

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.109322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 53408f9d-ff41-442a-8341-0cde2b74fdcf · outbound

This paper cites Deep hidden physics models: Deep learning of nonlinear partial differential equations.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Deep hidden physics models: Deep learning of nonlinear partial differential equations

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.090453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation efda763e-f660-4f25-8e20-ede35b963568 · outbound

This paper cites Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-14T11:26:49.482305Z

Source-reported events for the cited work

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Observation ccc905ea-1795-4035-b89f-ad40cbeba2d4 · outbound

This paper cites Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-14T11:26:49.490356Z

Source-reported events for the cited work

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Observation 4df8baaa-206b-4588-8dd8-605ff682d098 · outbound

This paper cites Anuga user manual, release 2.0.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Anuga user manual, release 2.0

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.072121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 79efe5f1-1389-4d3c-97ba-c1e9362b2313 · outbound

This paper cites E., Hinton, G.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development E., Hinton, G

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.054201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 70768295-dca3-4e0d-a543-fd70c02545e2 · outbound

This paper cites T., Yurekli, K., Pal, M., 2012.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development T., Yurekli, K., Pal, M., 2012

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.037198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e501d4b4-4c1e-4206-af0c-c4d2561c71f3 · outbound

This paper cites R., 1996.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development R., 1996

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.019955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 96366db1-cf43-48da-94c9-ec48c0e32b7c · outbound

This paper cites Dgm: A deep learning algorithm for solving partial differential equations.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Dgm: A deep learning algorithm for solving partial differential equations

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:50.000797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 850477b0-9023-46de-b05e-a5569c394c8c · outbound

This paper cites Decentralized Flood Forecasting Using Deep Neural Networks.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Decentralized Flood Forecasting Using Deep Neural Networks

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-08-14T11:26:49.692646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3d81f38b-ed10-4969-ad01-625afedce7da · outbound

This paper cites Shallow water hydrodynamics: Mathematical theory and numerical solution for a two-dimensional system of shallow-water equations.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Shallow water hydrodynamics: Mathematical theory and numerical solution for a two-dimensional system of shallow-water equations

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:49.981247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f52dfaf9-98cd-44c8-88a0-1b01df580e84 · outbound

This paper cites Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-14T11:26:49.536798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41531a41-78ef-4c0a-811c-f71af91d2ede · outbound

This paper cites Accelerating eulerian fluid simulation with convolutional networks.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Accelerating eulerian fluid simulation with convolutional networks

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:49.961209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 49e505ad-1fb3-4c0f-a459-9a59481a11aa · outbound

This paper cites Accelerating eulerian fluid simulation with convolutional networks.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Accelerating eulerian fluid simulation with convolutional networks

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:49.940828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 15fdf5a8-693f-4a7d-a405-895659bb4dc3 · outbound

This paper cites E., Behbahani, S.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development E., Behbahani, S

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:49.922592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4926040f-e301-4c6d-8075-ccc8f1901f7e · outbound

This paper cites E., Behbahani, S.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development E., Behbahani, S

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:49.904008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 243bbcd0-96db-41d5-b0a5-1418ec093b9e · outbound

This paper cites B., 2013.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development B., 2013

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:49.884684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e60af9f7-0d7b-45f2-a729-29164ea18ad7 · outbound

This paper cites Latent-space Physics: Towards Learning the Temporal Evolution of Fluid Flow.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Latent-space Physics: Towards Learning the Temporal Evolution of Fluid Flow

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-14T11:26:49.572659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a2e1484-b7ba-443a-bfad-4207d09bdb41 · outbound

This paper cites tempogan: A temporally coherent, volumetric gan for super-resolution fluid flow.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development tempogan: A temporally coherent, volumetric gan for super-resolution fluid flow

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:49.864100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6ae21d43-967e-4104-b03a-4f56a417fdb6 · outbound

This paper cites Y., O'connor, K.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Y., O'connor, K

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:49.844402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fd8e93c9-7383-48e6-9016-e8481a80c99e · outbound

This paper cites Markov flow models and the flood warning problem.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Markov flow models and the flood warning problem

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:49.825566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8e077f19-1d18-4461-bbde-4d7399233ef5 · outbound

This paper cites Catastrophic collapse of water supply reservoirs in urban areas.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Catastrophic collapse of water supply reservoirs in urban areas

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:26:49.805963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Outbound references

Pith citing papers