Results 81 to 90 of about 3,129 (263)

Stochastic differential game for management of non-renewable fishery resource under model ambiguity

Journal of Biological Dynamics, 2018
A new bio-economic model for managing population of non-renewable inland fishery resource in uncertain environment is presented. Population dynamics of the resource is described with stochastic differential equations (SDEs) having ambiguous growth and ...
Hidekazu Yoshioka, Yuta Yaegashi
doaj   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Promotion strategies for environmentally friendly packaging: a stochastic differential game perspective. [PDF]

Int J Environ Sci Technol (Tehran), 2023
Wang C, Liu J, Fan R, Xiao L.
europepmc   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Dynamic Governance of Electric Vehicle Supply Chain Network Resilience Under Disruption Risks

Systems
In the context of multiple overlapping uncertainties, upstream disruptions in electric vehicle supply chain networks are becoming increasingly frequent. Given the dynamic and sudden nature of disruption risks, this paper introduces a stochastic stopping ...
Xuan Wang, Xiaoye Zhou, Meilin Zhu
doaj   +1 more source

Mean-Field Type Games between Two Players Driven by Backward Stochastic Differential Equations

Games, 2018
In this paper, mean-field type games between two players with backward stochastic dynamics are defined and studied. They make up a class of non-zero-sum, non-cooperating, differential games where the players’ state dynamics solve backward ...
Alexander Aurell
doaj   +1 more source

Research on Corporate Social Responsibility Coordination of Three-Tier Supply Chain Based on Stochastic Differential Game. [PDF]

Front Psychol, 2022
Yang M, Yang Z, Li Y, Liang X.
europepmc   +1 more source

Smart Flexible Tactile Sensors: Recent Progress in Device Designs, Intelligent Algorithms, and Multidisciplinary Applications

Advanced Intelligent Discovery, EarlyView.
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang, Ming Dong, Rongrong Bao, Caofeng Pan   +3 more
wiley   +1 more source

A Stochastic Differential Game in the Orthrant

Journal of Mathematical Analysis and Applications, 2002
This paper concerns a zero-sum stochastic differential game on the nonnegative orthrant. The corresponding dynamical systems is a stochastic differential equation where players control act only on the drift terms (and not on the diffusion term), also the bijectories are reflected on the boundary of the orthrant.
Ghosh, Mrinal K, Kumar, Suresh K
openaire   +2 more sources

Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai, Yefeng Yang, Tao Huang, Boyang Li   +3 more
wiley   +1 more source