Customer segmentation in the digital marketing using a Q-learning based differential evolution algorithm integrated with K-means clustering. [PDF]
Wang G.
europepmc +1 more source
Objective We examined associations of post‐traumatic stress disorder (PTSD) and other mental health disorders (OMH) with rheumatoid arthritis (RA), accounting for effects of smoking. Methods We conducted a matched case‐control study, identifying incident RA cases and controls using national Veteran Health Administration data (2006‐2019).
Kelsey Coziahr +15 more
wiley +1 more source
A novel differential evolution algorithm with multi-population and elites regeneration. [PDF]
Cao Y, Luan J.
europepmc +1 more source
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
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 +2 more
wiley +1 more source
An optimized differential evolution algorithm for constitutive model fitting of arteries. [PDF]
Razian SA, Jadidi M.
europepmc +1 more source
Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane +3 more
wiley +1 more source
An improved differential evolution algorithm for multi-modal multi-objective optimization. [PDF]
Qu D, Xiao H, Chen H, Li H.
europepmc +1 more source
Differential evolution algorithm for performance optimization of the micro plasma actuator as a microelectromechanical system. [PDF]
Omidi J, Mazaheri K.
europepmc +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
Multi-UAV Cooperative Coverage Search for Various Regions Based on Differential Evolution Algorithm. [PDF]
Zeng H, Tong L, Xia X.
europepmc +1 more source

