Results 71 to 80 of about 3,165 (265)

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

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 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

Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining

Advanced Intelligent Systems, EarlyView.
Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson, Nebojša Maleševic, Anders Björkman, Christian Antfolk   +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

Adaptive Control of Run‐and‐Tumble Escape in Pursuit‐Evasion Dynamics of Intelligent Active Particles

Advanced Intelligent Systems, EarlyView.
The pursuit‐evasion game is studied for two adversarial active agents, modeled as deterministic self‐steering pursuer and stochastic, cognitive evader. For a successful evasion strategy, the motile target has to exploit all available pursuer information, e.g., by tuning the tumbling frequency with the pursuer distance.
Segun Goh, Dennis Haustein, Gerhard Gompper   +2 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

Data‐Driven Review and Machine Learning Prediction of Diamond Vacancy Center Synthesis

Advanced Intelligent Systems, EarlyView.
A machine learning framework is applied to photoluminescence spectra to extract linewidths and uncover how NV, SiV, GeV, and SnV centers evolve with growth and processing conditions. Unified normalization and k‐fold validation reveal cross‐method trends and enable rapid prediction of defect size and fabrication parameters, offering a data‐driven route ...
Zhi Jiang, Marco Peres, Carlo Bradac, Gil Gonçalves   +3 more
wiley   +1 more source