Uniqueness of solution to stochastic scalar conservation laws on bounded domain

This paper is concerned with the uniqueness of stochastic entropy solutions for stochastic scalar conservation law forced by a multiplicative noise on a bounded domain with a non-homogeneous boundary condition. The uniqueness is obtained by using the method of Kruzhkov?s doubling variables.

Authors

Institutions

Publication Details

Journal
Filomat
Published
2025-01-01
DOI
https://doi.org/10.2298/fil2509845z
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Uniqueness of solution to stochastic scalar conservation laws on bounded domain

Guangying Lv, Jing Zhang
Filomat
Stochastic processes and financial applications
article

Uniqueness of solution to stochastic scalar conservation laws on bounded domain

Guangying Lv, Jing Zhang
article en

Abstract

This paper is concerned with the uniqueness of stochastic entropy solutions for stochastic scalar conservation law forced by a multiplicative noise on a bounded domain with a non-homogeneous boundary condition. The uniqueness is obtained by using the method of Kruzhkov?s doubling variables.

FilomatVol. 39(9)
Nanjing University of Information Science and Technology (CN), Yellow River Conservancy Technical Institute (CN)
National Science Foundation, National Natural Science Foundation of China, Government of Jiangsu Province, Education Department of Henan Province, Qinglan Project of Jiangsu Province of China
Life in Land
Openalex Percentile: Top 73%
Stochastic processes and financial applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.