Results 121 to 130 of about 324,021 (282)

An Improved Q-Learning-Based Sensor-Scheduling Algorithm for Multi-Target Tracking. [PDF]

Sensors (Basel), 2022
Qu Z, Zhao X, Xu H, Tang H, Wang J, Li B.   +5 more
europepmc   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

Joint routing and hybrid traffic scheduling algorithm based on time-aware and cyclic queued forwarding in TSN

Tongxin xuebao
In order to solve the problem of hybrid scheduling of multiple time-sensitive flows in time-sensitive network(TSN), a TSN joint routing and hybrid traffic scheduling algorithm based on time-aware and cyclic queued forwarding was proposed.
WANG Ying, ZHUANG Zhihan, YU Peng, QIU Xuesong, GUO Shaoyong   +4 more
doaj  

Limited Duplication-Based List Scheduling Algorithm for Heterogeneous Computing System. [PDF]

Micromachines (Basel), 2022
Guo H, Zhou J, Gu H.
europepmc   +1 more source

A Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller

International Journal of Adaptive Control and Signal Processing, EarlyView.
Block Diagram of the Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller. ABSTRACT This article introduces a discrete‐time robust adaptive one‐sample‐ahead preview super‐twisting sliding mode controller. A stability analysis of the controller by Lyapunov criteria is developed to demonstrate its robustness in handling both ...
Guilherme Vieira Hollweg, Paulo Jefferson Dias de Oliveira Evald, Shivam Chaturvedi, Hilton Abilio Gründling, Rodrigo Varella Tambara, Wencong Su   +5 more
wiley   +1 more source

Trust-aware dynamic level scheduling algorithm in cloud environment

Tongxin xuebao, 2014
Based on interpersonal trust model in sociology，a trust evaluation model is proposed based on users’ past experience with service provider，friends’ recommendations and third party’s feedback.By combining users’ trust requirement for service resource ...
Jie CAO, Guo-sun ZENG, Huo-wen JIANG, Hai-ying MA   +3 more
doaj   +2 more sources

Persistent Periodic Uplink Scheduling Algorithm for Massive NB-IoT Devices. [PDF]

Sensors (Basel), 2022
Wu TY, Hwang RH, Vyas A, Lin CY, Huang CR.   +4 more
europepmc   +1 more source

Optimal schedules for annealing algorithms

Physical Review E
Annealing algorithms such as simulated annealing and population annealing are widely used both for sampling the Gibbs distribution and solving optimization problems (i.e. finding ground states). For both statistical mechanics and optimization, additional parameters beyond temperature are often needed such as chemical potentials, external fields or ...
Amin Barzegar, Firas Hamze, Christopher Amey, Jonathan Machta   +3 more
openaire   +3 more sources

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

A Two-Workshop Collaborative, Integrated Scheduling Algorithm considering the Prescheduling of the Root-Subtree Processes. [PDF]

Comput Intell Neurosci, 2022
Xie Z, Teng H, Ming J, Yue X.
europepmc   +1 more source