Two approaches detect EV charging patterns at stations.
problem Identify charging patterns at electric vehicle charging stations.
method Two approaches: rule-based and hierarchical clustering.
result Hierarchical clustering revealed unexpected charging patterns.
Develops a combinatorial semi-bandit method for electric vehicle charging station selection.
problem Long-distance navigation for BEVs with unknown charging station availability and performance.
method Combinatorial semi-bandit framework, pre-processing road network, Bayesian modeling, Thompson Sampling, BayesUCB, Epsilon-greedy.
result Demonstrates improved navigation performance on long-distance BEV charging station selection.
Electric vehicles (EVs) have been gaining popularity due to their environmental friendliness and efficiency. EV charging station networks are scalable solutions for supporting increasing numbers of EVs within modern electric grid constraints, yet few tools exist to aid the physical configuration design of new networks.…
Challenge forecasts EV charging station usage accurately.
problem Better understanding of EV charging behaviors needed.
method Hierarchical forecasting of EV charging station occupancy.
result Hierarchical forecasting improves EV charging station occupancy predictions.
A federated graph learning approach improves EV charging demand forecasting while protecting against cyberattacks.
problem Cybersecurity risk and data heterogeneity in EV charging demand forecasting.
method Federated Graph Neural Network (GNN) model with global attention mechanism and credit-based function.
result Enhanced robustness and prediction accuracy in EV charging demand forecasting.
Kernel-based mean-field games use MMD penalties for interaction and target costs.
problem Optimizing mean-field games with specific cost functions.
method Kernel structure, random Fourier U-statistics, neural network training.
result Sample-level convergence theorem and rate of convergence proved.
PIML uses physics equations in machine learning for better forecasting.
problem Forecasting time series data with physical constraints.
method Physics-informed neural networks (PINNs) and kernel methods.
result PIML improves forecasting accuracy with physical constraints.
The paper proves a new theorem linking mass and electric charge for certain types of manifolds.
problem Proving a new positive mass theorem for manifolds with charge.
method Using conformal relations and scalar curvature, the authors derive a new theorem.
result The sum of mass is not less than the modulus of total electric charge under certain conditions.
Bayesian model for energy consumption helps electric vehicles navigate efficiently.
problem Limited battery capacity in electric vehicles makes energy efficient navigation challenging.
method Developed an online learning framework using Bayesian models and exploration strategies like Thompson Sampling.
result Established rigorous regret bounds for Thompson Sampling in both single-agent and multi-agent settings.
The Lorentz force equations provide a partial description of the geodesic motion of a charged particle on a four-manifold. Under the hypothesis that Maxwell's equations express symmetry properties of the Ricci tensor, the full electromagnetic connection is determined. From this connection, the fourth equation of the ge…
The article proves charged quasi-local Penrose inequalities for compact manifolds with boundary.
problem Determining if a quasi-local version of the Riemannian Penrose inequality holds for Einstein-Maxwell equations.
method Building on ideas of Lu and Miao, and the first-named author, the article proves charged quasi-local Penrose inequalities for a class of compact manifolds with boundary.
result The lower bound on quasi-local mass is exactly the lower bound on the ADM mass given by the charged Riemannian Penrose inequality for a specific reference manifold.
FedGAN trains GANs across distributed data sources with reduced communication.
problem Training GANs across non-independent data sources with privacy and communication constraints.
method FedGAN uses local generators and discriminators synced via an intermediary, proving convergence under standard assumptions.
result FedGAN converges and performs similarly to general distributed GANs with reduced communication complexity.
Bayesian model for energy-efficient EV navigation.
problem Limited battery capacity in electric vehicles.
method Bayesian modeling and online learning framework with exploration strategies.
result Established rigorous regret bounds for Thompson Sampling.
Study on implied certainty equivalent rates in financial markets and electric vehicles.
problem Investment risk in financial markets.
method Mathematical derivation of implied certainty equivalent rate, empirical analysis of stock and option data.
result Positive implied certainty equivalent rates are more suitable for investment than negative ones, but higher values increase risk.
This paper constructs charged Riemannian manifolds to test Penrose inequality.
problem Testing the Riemannian Penrose Inequality with charged manifolds.
method Constructing asymptotically hyperbolic or Euclidean extensions with electric charge.
result Suggests instability of the generalized Riemannian Penrose Inequality.
Initial DR studies mainly adopt model predictive control and thus require accurate models of the control problem (e.g., a customer behavior model), which are to a large extent uncertain for the EV scenario. Hence, model-free approaches, especially based on reinforcement learning (RL) are an attractive alternative. In t…
The paper explores how topological methods can reveal insights into electric charge distributions on knots.
problem Understanding the qualitative behavior of electric potentials on knots.
method Geometric topology techniques applied to electrostatics.
result Proved a lower bound on the size of the critical set based on knot projections.
Deep learning solves EV routing with time windows for EV fleets.
problem Electric vehicle routing with time windows for logistics.
method End-to-end deep reinforcement learning with attention model and graph embedding.
result Proposed model efficiently solves large EVRPTW instances.
Positive energy theorems for spin initial data with charge in higher dimensions.
problem Establishing positive energy theorems for spin initial data with charge in dimensions n≥4. method Using a dominant energy condition and asymptotically flat ends, extending classical theorems.
result Extending classical positive energy theorems to spin initial data with charge.
Throughout the literature on the charged Riemannian Penrose inequality, it is generally assumed that there is no charged matter present; that is, the electric field is divergence-free. The aim of this article is to clarify when the charged Riemannian Penrose inequality holds in the presence of charged matter, and when …
A necessary and sufficient condition for energy-momentum conservation is proved within a topological, pre-metric approach to classical electrodynamics including magnetic as well as electric charges. The extended Lorentz force, consisting of mutual actions by F=(E, B) on the electric current and G=(H, D) on the magnetic…
Recent changes to greenhouse gas emission policies are catalyzing the electric vehicle (EV) market making it readily accessible to consumers. While there are challenges that arise with dense deployment of EVs, one of the major future concerns is cyber security threat. In this paper, cyber security threats in the form o…
In this letter, we address the problem of controlling energy storage systems (ESSs) for arbitrage in real-time electricity markets under price uncertainty. We first formulate this problem as a Markov decision process, and then develop a deep reinforcement learning based algorithm to learn a stochastic control policy th…
Paper models and forecasts intra-day electricity price spreads.
problem Forecasting intra-day price spreads for electricity traders and operators.
method Dynamic density functions based on skewed-t distributions, conditional on exogenous drivers.
result Best fitting and forecasting specifications selected using Pinball Loss function.
We establish a class of area-angular momentum-charge inequalities satisfied by stable marginally outer trapped surfaces in 5-dimensional minimal supergravity which admit a U(1)2 symmetry. A novel feature is the fact that such surfaces can have the nontrivial topologies S1×S2 and L(p,q). In addition to t…
Survey of reinforcement learning for sustainable energy challenges.
problem Sequential decision-making challenges in sustainable energy.
method Reinforcement learning applied to energy production, storage, transmission, and consumption.
result Survey identifies various reinforcement learning themes and potential future directions.
Adversarial attacks degrade DRL-based EV energy management systems.
problem Adversarial attacks on DRL-based energy management systems of electric vehicles.
method Generated adversarial examples to degrade DRL performance using low-dimensional state representations.
result Adversarial attacks can significantly degrade DRL-based EV energy management systems.
No time-periodic Majorana fermions found in Kerr-Newman spacetimes with nontrivial charge.
problem Existence of Majorana fermions in Kerr-Newman spacetimes with nontrivial charge.
method Analysis of Dirac equation in Kerr-Newman spacetimes, leading to algebraic identities.
result No differentiable time-periodic Majorana fermions in Kerr-Newman spacetimes with nontrivial charge.
CapOptix uses options theory to price capacity in electricity markets.
problem Traditional capacity market designs fail to account for risk and price shocks.
method Interprets capacity commitments as reliability options and uses Markov Regime Switching Process.
result CapOptix provides more accurate pricing of capacity premia compared to existing mechanisms.
We prove existence of all possible bi-axisymmetric near-horizon geometries of 5-dimensional minimal supergravity. These solutions possess the cross-sectional horizon topology S3, S1×S2, or L(p,q) and come with prescribed electric charge, two angular momenta, and a dipole charge (in the ring case). Moreov…
Study electric field and potential of torus knots, focusing on z-axis.
problem Analyze electric field and potential of torus knots.
method Parametrize torus knots, use symmetry, numerical methods, contour integration.
result Electric field is zero only at the origin, extreme points analyzed.
An analytic extension of the Reissner-Nordstrom solution at and beyond the singularity is presented. The extension is obtained by using new coordinates in which the metric becomes degenerate at r=0. The metric is still singular in the new coordinates, but its components become finite and smooth. Using this extension …
Deep Q-learning optimizes same-day delivery with vehicles and drones.
problem Optimizing same-day delivery with limited vehicle and drone capacities.
method Deep Q-learning approach to assign packages to vehicles or drones.
result Deep Q-learning policy outperforms benchmark policies and maintains effectiveness with changing fleet sizes.
The paper explores rigid geometric structures near surfaces with equality in area-charge inequalities.
problem Geometric constraints near surfaces with equality in area-charge inequalities.
method Investigation of equality in area-charge inequalities for spherical minimal surfaces and MOTS within the Einstein-Maxwell equations framework.
result Equality in area-charge inequalities imposes rigid geometric structures, including normal electric and magnetic fields and isometric Riemannian products.
Optimizes electric aircraft deployment for Canadian aviation to reduce emissions.
problem Limited fleet capacity and operational structure hinder electric aircraft transition.
method Multi-period mixed-integer linear programming (MILP) framework.
result Electric aircraft can reduce emissions by over 70% within five years.
Constructs solutions to Einstein-Maxwell-current system using Sasakian manifolds.
problem Solving the Einstein-Maxwell-Current system with inhomogeneous charged particle density.
method Using Sasakian manifolds to specify magnetic field and electric current.
result Solutions with arbitrary function describing charged particle density and curvature.
Let A be the space of irreducible connections (vector potentials) over a SU(n)-principal bundle on a three-dimensional manifold M. Let T be the fiber product of the tangent and cotangent bundles of A. We endow T with a symplectic structure Ωwhich is represented by a vortex formula. The corresponding Poisson bracket wil…
Adapts model-based advice to stabilize black-box policies for nonlinear control.
problem Stabilizing machine-learned policies for nonlinear control with limited model information.
method Proposes an adaptive λ-confident policy to combine black-box and model-based advice. result Proves the stability of the adaptive λ-confident policy and its competitive ratio. Making use of the Kerr theorem for shear-free null congruences and of Newman's representation for a virtual charge ``moving'' in complex space-time, we obtain an axisymmetric time-dependent generalization of the Kerr congruence, with a singular ring uniformly contracting to a point and expanding then to infinity. Elect…
Modern machine learning techniques, such as convolutional, recurrent and recursive neural networks, have shown promise for jet substructure at the Large Hadron Collider. For example, they have demonstrated effectiveness at boosted top or W boson identification or for quark/gluon discrimination. We explore these methods…
Study electric-magnetic duality in M-theory compactifications.
problem Restoring supersymmetry and understanding dualities in compactified M-theory.
method Dualizing M-theory on G2 manifolds with F-theory and studying D3-branes. result Demonstrates correspondence between D3-branes and shrinking surfaces/curves, revealing light particles with electric and magnetic charges.
Closed and broken electromagnetic orbits in Kerr-Newman spacetime
problem Constructing closed and broken electromagnetic orbits in the Kerr-Newman spacetime
method Constructing smooth closed electromagnetic orbits tangent to the axial Killing field and proving the existence of spherical electromagnetic orbits
result Proving the existence of spherical electromagnetic orbits and constructing closed broken electromagnetic orbits
A novel controller for wheeled robots handles joystick inputs for smooth steering.
problem Steering control for differential-drive wheeled robots from indirect joystick inputs.
method Developed a geometric controller based on Darboux frame kinematics.
result Smooth trajectories achieved with safety constraints and no desired states.
This paper uses t-SNE to visualize multi-objective electric machine optimization at various operating points.
problem Visualization of multi-objective electric machine optimization at multiple operating points is challenging.
method Utilizes t-distributed stochastic neighbor embedding (t-SNE) to visualize high-dimensional data.
result t-SNE provides better visualizations of electric machine design candidates and their performance.
In the paper [4] is presented a theory which unifies the gravitation theory and the mechanical effects, which is different from the Riemannian theories like GTR. Moreover it is built in the style of the electomagnetic field theory. This paper is a continuation of [4] such that the complex variant of that theory yields …
We construct a covariant functor from a category of Abelian principal bundles over globally hyperbolic spacetimes to a category of *-algebras that describes quantized principal connections. We work within an appropriate differential geometric setting by using the bundle of connections and we study the full gauge group,…
We count the supersymmetric bound states of many distinct BPS monopoles in N=4 Yang-Mills theories and in pure N=2 Yang-Mills theories. The novelty here is that we work in generic Coulombic vacua where more than one adjoint Higgs fields are turned on. The number of purely magnetic bound states is again found to be cons…
In this paper we present an econophysic model for the description of shares transactions in a capital market. For introducing the fundamentals of this model we used an analogy between the electrical field produced by a system of charges and the overall of economic and financial information of the shares transactions fr…