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RGCNdist2vec: Using Graph Convolutional Networks and Distance2Vector to Estimate Shortest Path Distance Along Road Networks
Computing shortest distance estimation for road networks is an important component of map service systems. Existing embedded-based shortest path...
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A comparative assessment of tree-based predictive models to estimate geopolymer concrete compressive strength
Fly ash-based geopolymer concrete (FA-GPC) is a material that might be utilized to build a more sustainable construction industry; therefore, this...
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A fast Fourier-Galerkin method solving boundary integral equations for the Helmholtz equation with exponential convergence
A boundary integral equation in general form will be considered, which can be used to solve Dirichlet problems for the Helmholtz equation. The goal...
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The strong convergence and stability of explicit approximations for nonlinear stochastic delay differential equations
This paper focuses on explicit approximations for nonlinear stochastic delay differential equations (SDDEs). Under less restrictive conditions, the...
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Inertial randomized Kaczmarz algorithms for solving coherent linear systems
In this paper, by regarding the two-subspace Kaczmarz method as an alternated inertial randomized Kaczmarz algorithm we present a better convergence...
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Convergence analysis of sample average approximation for a class of stochastic nonlinear complementarity problems: from two-stage to multistage
In this paper, we consider the sample average approximation (SAA) approach for a class of stochastic nonlinear complementarity problems (SNCPs) and...
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Convergence of an adaptive modified WG method for second-order elliptic problem
In this paper, an adaptive modified weak Galerkin (AMWG) method is considered to solve second-order elliptic problem. Under the assumption of a...
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Adaptive full order sliding mode control for electronic throttle valve system with fixed time convergence using extreme learning machine
This paper proposes a novel extreme learning machine (ELM)-based fixed time adaptive trajectory control for electronic throttle valve system with...
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Free-Rider Problem: Simulating of System Convergence to Stable Equilibrium State by Means of Finite Markov Chain Models
The paper suggests a new approach to classic economic problem – “the problem of free-rider”. This well – known problem deals with a process of...
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Distributed Averaging for Accuracy Prediction in Networked Systems
Distributed averaging is among the most relevant cooperative control problems, with applications in sensor and robotic networks, distributed signal...
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Families of high-order simultaneous methods with several corrections
In this paper, we propose the idea for combining several iteration functions in order to construct new families of iterative methods with both...
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Recommendation system for technology convergence opportunities based on self-supervised representation learning
We show how a deep neural network can be designed to learn meaningful representations from high-dimensional and heterogeneous categorical features in...
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Bayesian Modeling for a Shape Parameter of Weibull-Lomax Distribution with an Application to Health Data
In this paper, effective Bayesian estimation procedures have been explored to estimate a shape parameter of the Weibull-Lomax distribution with the...
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Adaptive Echo State Network Robot Control with Guaranteed Parameter Convergence
Most existing adaptive neural network (NN) robot control methods suffer from poor convergence performance of network weights, which cannot fully...
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On the Convergence of DEM’s Linear Parameter Estimator
The free energy principle from neuroscience provides an efficient data-driven framework called the Dynamic Expectation Maximization (DEM), to learn...
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Mean-square convergence of numerical methods for random ordinary differential equations
The aim of this work is to analyze the mean-square convergence rates of numerical schemes for random ordinary differential equations (RODEs). First,...
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A Convergence with Computer Science
Prior to the latter part of the twentieth century, the field of scientific visualization was both technical illustration [1, 2] and analytic geometry...
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Data-driven cooperative optimal output regulation for linear discrete-time multi-agent systems by online distributed adaptive internal model approach
In this study, a data-driven learning algorithm was developed to estimate the optimal distributed cooperative control policy, which solves the...
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Convergence Proof for Actor-Critic Methods Applied to PPO and RUDDER
We prove under commonly used assumptions the convergence of actor-critic reinforcement learning algorithms, which simultaneously learn a policy...