139,271 Hits in 3.8 sec

Data-based Discovery of Governing Equations [article]

Waad Subber, Piyush Pandita, Sayan Ghosh, Genghis Khan, Liping Wang, Roger Ghanem
2020 arXiv   pre-print
We propose a Data-based Physics Discovery (DPD) framework for automatic discovery of governing equations from observed data.  ...  In case a prior model is not available, the DPD framework discovers a new data-based standalone model governing the observations.  ...  Acknowledgments The authors thank the United States Air Force Research Laboratory for providing the corrosion data for public release under Distribution A as defined by the United States Department of  ... 
arXiv:2012.06036v2 fatcat:2jtqz2srofeinoaxj7wz3in2qe

Paradigm Shift Through the Integration of Physical Methodology and Data Science [article]

Takashi Miyamoto
2021 arXiv   pre-print
scientific methodologies while revealing unprecedented challenges such as the interpretability of computations and the demand for extrapolative predictions on the amount of data.  ...  Methods that integrate traditional physical and data science methodologies are new methods of mathematical analysis that complement both methodologies and are being studied in various scientific fields  ...  (d)Solving the governing equations using data-driven models (e)Physics-based loss functions (f)Data-driven construction of governing equations (g)Reflecting physical knowledge in model architectures (h  ... 
arXiv:2110.01408v1 fatcat:jndzsb3krja7bhearq75tog2xy

Visual Physics: Discovering Physical Laws from Videos [article]

Pradyumna Chari, Chinmay Talegaonkar, Yunhao Ba, Achuta Kadambi
2019 arXiv   pre-print
These elementary tasks have textbook governing equations and enable ground truth verification of our approach.  ...  The problem is very difficult because a machine must learn not only a governing equation (e.g. projectile motion) but also the existence of governing parameters (e.g. velocities).  ...  Defining "discovery of physics": We define discovery of physics as discovering both the governing parameters and governing equations.  ... 
arXiv:1911.11893v1 fatcat:ilzvb33jjjhgvcisnsgkfbcgrm

Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning [article]

Chengping Rao, Pu Ren, Yang Liu, Hao Sun
2022 arXiv   pre-print
regression with the reconstructed data to identify the explicit form of the governing PDEs.  ...  Although past research attempts have achieved great success in data-driven PDE discovery, the robustness of the existing methods cannot be guaranteed when dealing with low-quality measurement data.  ...  Well formulated governing equations facilitate scientific discovery and promote establishment of new disciplines.  ... 
arXiv:2201.12354v1 fatcat:lks4nimsxfbcvc7522l4ob7opu

Distilling Governing Laws and Source Input for Dynamical Systems from Videos [article]

Lele Luan, Yang Liu, Hao Sun
2022 arXiv   pre-print
This paper introduces an end-to-end unsupervised deep learning framework to uncover the explicit governing equations of dynamics presented by moving object(s), based on recorded videos.  ...  closed-form governing equations from the learned physical states.  ...  BJJWZYJH012019100020098) as well as the Intelligent Social Governance Platform, Major Innovation & Planning Interdisciplinary Platform for the "Double-First Class" Initiative, Renmin University of China  ... 
arXiv:2205.01314v1 fatcat:3phl67o63fdwfl5fai2ocbrcvy

Any equation is a forest: Symbolic genetic algorithm for discovering open-form partial differential equations (SGA-PDE) [article]

Yuntian Chen, Yingtao Luo, Qiang Liu, Hao Xu, Dongxiao Zhang
2021 arXiv   pre-print
However, the PDEs of many real-world problems are uncertain, which calls for PDE discovery.  ...  We propose the symbolic genetic algorithm (SGA-PDE) to discover open-form PDEs directly from data without prior knowledge about the equation structure.  ...  Acknowledgements This work is partially funded by the Shenzhen Key Laboratory of Natural Gas Hydrates (Grant No.  ... 
arXiv:2106.11927v1 fatcat:3b77fga6anfdhb5jnupln3ymau

Uncovering Closed-form Governing Equations of Nonlinear Dynamics from Videos [article]

Lele Luan, Yang Liu, Hao Sun
2021 arXiv   pre-print
Although discovery of governing equations based on observed system states (e.g., trajectory time series) has revealed success in a wide range of nonlinear dynamics, uncovering the closed-form equations  ...  closed-form governing equations of learned physical states and, meanwhile, serves as a constraint to the autoencoder.  ...  Data-driven discovery of coordinates and governing equations.  ... 
arXiv:2106.04776v1 fatcat:wdwnarduazeexkwj3durc63dk4

Data-driven discovery of coordinates and governing equations

Kathleen Champion, Bethany Lusch, J. Nathan Kutz, Steven L. Brunton
2019 Proceedings of the National Academy of Sciences of the United States of America  
The discovery of governing equations from scientific data has the potential to transform data-rich fields that lack well-characterized quantitative descriptions.  ...  This method places the discovery of coordinates and models on an equal footing.  ...  The traditional derivation of governing equations is based on underlying first principles, such as conservation laws and symmetries, or from universal laws, such as gravitation.  ... 
doi:10.1073/pnas.1906995116 pmid:31636218 pmcid:PMC6842598 fatcat:m4swjd6e25b77p6bdpwb2mlgxa

DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data [article]

Hao Xu, Haibin Chang, Dongxiao Zhang
2020 arXiv   pre-print
To overcome these challenges, in this work, a deep-learning based data-driven method, called DL-PDE, is developed to discover the governing PDEs of underlying physical processes.  ...  The DL-PDE method combines deep learning via neural networks and data-driven discovery of PDE via sparse regressions.  ...  In recent years, data-driven discovery of governing equations of physical problems has attracted much attention.  ... 
arXiv:1908.04463v2 fatcat:nlggpvtm2je4hkwniwbj7kk3r4

On spike-and-slab priors for Bayesian equation discovery of nonlinear dynamical systems via sparse linear regression [article]

Rajdip Nayek, Ramon Fuentes, Keith Worden, Elizabeth J. Cross
2020 arXiv   pre-print
This paper presents the use of spike-and-slab (SS) priors for discovering governing differential equations of motion of nonlinear structural dynamic systems.  ...  Three different variants of SS priors are explored for performing Bayesian equation discovery.  ...  A magnitude-based weight-thresholding was combined with RVM in [14] for discovery of governing partial differential equations.  ... 
arXiv:2012.01937v2 fatcat:5qpkyyof4zeo7gxb42tw7i4bm4

Price Discovery Pada Pasar Obligasi Pemerintah Indonesia

Buddi Wibowo
2021 Jurnal Manajemen, Strategi Bisnis dan Kewirausahaan  
The study investigate price discovery in Indonesia government bond market. Understanding price discovery is a must to identify relevant factor affecting price of the asset.  ...  The results show that from the two layers of order flow, the short-term dealer order flow and short-term customer order flow have role in price discovery process.  ...  METHOD The data for this research is obtained from transaction data of government bond from Ministry of Finance of the Republic of Indonesia.  ... 
doi:10.24843/matrik:jmbk.2021.v15.i02.p02 fatcat:hgmhwwsav5fd3adawtbij36aiy

Robust physics discovery via supervised and unsupervised pattern recognition using the Euler characteristic [article]

Zhiming Zhang, Yongming Liu
2021 arXiv   pre-print
We also demonstrate that the machine learning approaches using EC can improve the confidence level of sparse regression methods of physics discovery.  ...  Existing approaches, however, still lack robustness, especially when the measured data contain a large level of noise.  ...  The robustness of the data-driven physics discovery using ECs has been verified with data containing a wide range of levels of measurement noise.  ... 
arXiv:2110.13610v1 fatcat:vz3jqscduzgdzbgz7bm23nfxdm

Automated Discovery of Biological Models via Universal Differential Equations [article]

Christopher Rackauckas
Automated Discovery of Biological Models via Universal Differential Equations Christopher Rackauckas In the context of science, the well-known adage "a picture is worth a thousand words" might well be  ...  We show how UDEs can be utilized to discover previously unknown governing equations, accurately extrapolate beyond the original data, and accelerate model simulation, all in a time and data-efficient manner  ...  "Discovering governing equations from data by sparse identification of nonlinear dynamical systems." Proceedings of the national academy of sciences 113.15 (2016): 3932-3937.  ... 
doi:10.6084/m9.figshare.12881840.v2 fatcat:kzfh33i7tzcwld6gkgsdwziase

Data-driven identification of parametric partial differential equations [article]

Samuel Rudy, Alessandro Alla, Steven L. Brunton, J. Nathan Kutz
2018 arXiv   pre-print
In this work we present a data-driven method for the discovery of parametric partial differential equations (PDEs), thus allowing one to disambiguate between the underlying evolution equations and their  ...  This work builds on previous methods for the identification of constant coefficient PDEs, expanding the field to include a new class of equations which until now have eluded machine learning based identification  ...  The extraction of physical laws from experimental data, often in the form of differential and partial differential equations, may be critical to science and engineering applications where governing equations  ... 
arXiv:1806.00732v1 fatcat:ye6bn4fbfzeazoetulorp2q644

Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control [article]

Urban Fasel, J. Nathan Kutz, Bingni W. Brunton, Steven L. Brunton
2021 arXiv   pre-print
Sparse model identification enables the discovery of nonlinear dynamical systems purely from data; however, this approach is sensitive to noise, especially in the low-data limit.  ...  We apply this ensemble-SINDy (E-SINDy) algorithm to several synthetic and real-world data sets and demonstrate substantial improvements to the accuracy and robustness of model discovery from extremely  ...  Acknowledgments The authors acknowledge support from the Air Force Office of Scientific Research (AFOSR FA9550-19-1-0386), the Army Research Office (ARO W911NF-19-1-0045), and the National Science Foundation  ... 
arXiv:2111.10992v1 fatcat:exzyncydxncjvcvynf5rr7452a
« Previous Showing results 1 — 15 out of 139,271 results