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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,042 papers · 148 categories

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150299449598 · Jun 202019922001200920172026
48 results for qSH wave travel times

Paper recovers material parameters in transversely isotropic media under specific conditions.

problem Recovering material parameters in transversely isotropic media.
method Knowledge of qSH wave travel times determines the axis of isotropy and some elastic material parameters.
result Full determination of material parameters under certain conditions.

Researchers recover material parameters in transversely isotropic media from travel times of qP and qSV waves.

problem Recovering material parameters in transversely isotropic media from travel times of qP and qSV waves.
method Using parabolic type operators and stability estimates for travel times of qP and qSV waves.
result Stability estimates for recovering material parameters from travel times of qP and qSV waves.

Study shows curves converge to traveling waves under specific conditions.

problem Global stability of traveling waves for area-preserving curvature flow.
method Area-preserving curvature flow with contact angle condition.
result Moving curves converge to traveling waves starting from embedded convex curves.

Study traveling waves in hyperbolic space for Fisher-KPP equations.

problem Understanding wave behavior in hyperbolic space for Fisher-KPP equations.
method Analyzes the Cauchy problem in hyperbolic space for heat equation with Fisher-KPP forcing term.
result Proves new results on the dichotomy of solution propagation or vanishing based on diffusion and reaction strength.

The study finds solutions to a financial equation related to volatility.

problem Finding solutions to a financial equation related to volatility.
method Using a zero-curvature condition and soliton theory, the study derives a variant of the Harry Dym equation and finds its travelling wave solutions.
result A family of travelling wave solutions to a variant of the Harry Dym equation is found.

Develops methods to construct harmonic and wave maps into variable-curvature surfaces.

problem Limited explicit constructions for harmonic and wave maps in variable-curvature settings.
method Reduction framework for pseudo-Riemannian surfaces, geometric ansatz, first-order ODEs.
result Constructs explicit harmonic and wave maps into ellipsoids, hyperboloids, and Schwarzschild exterior.

Model for corporate bond pricing with credit rating migration, solving a double free boundary problem.

problem Corporate bond pricing with credit rating migration risks.
method Established a pricing model as a double free boundary problem, proving existence, uniqueness, and regularity of the solution.
result Two free boundaries are shown to be smooth and converge to a traveling wave solution as time goes to infinity.

Researchers recover Riemannian manifolds and lower order terms from travel time data.

problem Recovering Riemannian manifolds and lower order terms from travel time data.
method Adaptation of the Boundary Control method to recover lower order terms.
result Complete Riemannian manifolds and lower order terms can be uniquely recovered from a local source to solution map.

Researchers reconstruct simple Riemannian manifolds from boundary wave arrival times.

problem Reconstructing Riemannian manifolds from unknown interior sources and arrival times.
method Discrete metric approximation using labeled Gromov--Hausdorff distance.
result Finite-time approximations converge to the true Riemannian manifold.

We survey some results on travel time tomography. The question is whether we can determine the anisotropic index of refraction of a medium by measuring the travel times of waves going through the medium. This can be recast as geometry problems, the boundary rigidity problem and the lens rigidity problem. The boundary r…

2016-04-03abs ↗pdf ↗

Researchers prove injectivity and stability for mixed ray transform on simple manifolds.

problem Injectivity and stability of mixed ray transform for tensor fields.
method Analyzing tensor fields on 3D compact simple Riemannian manifolds with boundary.
result Injectivity and stability estimates for normal operator on generic 3D simple manifolds.

We establish sufficient conditions for existence of curves minimizing length as measured with respect to a degenerate metric on the plane while enclosing a specified amount of Euclidean area. Non-existence of minimizers can occur and examples are provided. This continues the investigation begun in [ABCDS] where the met…

2016-07-28abs ↗pdf ↗

Bayesian framework predicts post-disruption travel times in metro networks.

problem Uncertainty in post-disruption travel times in metro networks.
method Bayesian spatiotemporal modeling framework capturing train interactions and non-Gaussian distributional characteristics.
result The proposed models consistently outperform baseline specifications in point prediction and uncertainty quantification.

Paper addresses travel time tomography stability and statistical inversion.

problem Determining conformal factors of metrics from geodesic lengths.
method Established forward and inverse stability estimates; applied to Bayesian statistical inversion.
result Consistency of statistical inversion technique for travel time tomography.

Study uses neural networks to predict travel times for public transportation.

problem Inaccurate travel time predictions due to road traffic irregularities.
method Developed two neural network models (MLP and LSTM) using OD travel time matrix.
result Both models can make near-accurate predictions, but LSTM is more susceptible to noise.

This paper presents a bus travel time prediction system using deep neural networks.

problem Accurate travel time predictions for urban buses to compete with other modes of transport.
method Multi-output, multi-time-step deep neural network combining convolutional and LSTM layers.
result The proposed model significantly outperforms other methods and detects small irregular peaks quickly.

We study the boundary rigidity problem with partial data consisting of determining locally the Riemannian metric of a Riemannian manifold with boundary from the distance function measured at pairs of points near a fixed point on the boundary. We show that one can recover uniquely and in a stable way a conformal factor …

2013-06-12abs ↗pdf ↗

STAD improves travel time estimation by learning from real traffic data.

problem Travel time estimation using GPS traces is inaccurate and requires offline optimization.
method STAD uses machine learning and real-time trip data to adjust travel time estimates.
result STAD reduces median absolute errors by 14% in Doha and New York City, and 29% in Porto.

Boosting algorithms improve delivery time prediction in postal services.

problem Challenges in long-term travel time prediction for postal services.
method Investigated linear regression models, tree-based ensembles (random forest, bagging, boosting), and compared their performance.
result Boosting algorithms, especially light gradient boosting and catboost, outperform other methods in accuracy and runtime efficiency.

Model predicts travel time under rare conditions using a vector-space model.

problem Predicting travel time under rare temporal conditions (e.g., holidays, school vacations) is challenging due to limited historical data and other temporal changes.
method Presented a vector-space model for encoding rare temporal conditions, allowing coherent representation learning across different conditions.
result Increased performance for travel time prediction over different baselines when using the vector-space encoding for representing the temporal setting.

Two novel models predict bus travel times with uncertainty, improving connection assurance.

problem Improving bus connection assurance by handling travel time uncertainty.
method Two novel approaches: Deep Quantile Regression (DQR) and Bayesian Recurrent Neural Networks (BRNN).
result DQR model performs best for 80%, 90%, and 95% prediction intervals, with small underestimation.

Enhanced travel time prediction using deep neural networks and road network information.

problem Improving travel time estimation using deep learning models.
method Proposes incorporating road network information into deep learning models for travel time prediction.
result Improved travel time prediction, especially with limited training data.

Study travel time tomography for transversely isotropic media using modified pseudodifferential calculus.

problem Travel time tomography problem for transversely isotropic media.
method Modified scattering pseudodifferential calculus to solve the tomography problem.
result Construction and use of modified pseudodifferential calculus to solve the tomography problem.

Dynamic linear models improve travel time prediction for congested freeways.

problem Accurate travel time prediction for congested freeways.
method Dynamic linear models (DLMs) with time-varying parameters.
result Significant improvements in travel time prediction accuracy, especially for short-term predictions.

DeepIST uses CNNs to estimate travel time from path images.

problem Accurately estimating travel time for a path in urban transportation systems.
method Proposes DeepIST, a neural network framework that converts paths into generalized images and uses PathCNN and 1D CNN to capture spatial and temporal patterns.
result DeepIST significantly outperforms existing models in travel time estimation.