Evolutionary algorithms guided by Erdős-Rényi complex networks. [PDF]
Bucheli VA+2 more
europepmc +1 more source
Reinforcement learning-based pinning control for synchronization suppression in complex networks. [PDF]
Li K, Yang L, Guan C, Leng S.
europepmc +1 more source
Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez+2 more
wiley +1 more source
Study on the Stability of Complex Networks in the Stock Markets of Key Industries in China. [PDF]
Wang Z, Zhang G, Ma X, Wang R.
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
Finding influential nodes in complex networks based on Kullback-Leibler model within the neighborhood. [PDF]
Wang G, Sun Z, Wang T, Li Y, Hu H.
europepmc +1 more source
Performance Triggered Adaptive Model Reduction for Soil Moisture Estimation in Precision Irrigation
ABSTRACT Accurate soil moisture information is essential for precise irrigation to enhance water use efficiency. Estimating soil moisture based on limited soil moisture sensors is especially critical for obtaining comprehensive soil moisture information when dealing with large‐scale agricultural fields.
Sarupa Debnath+4 more
wiley +1 more source
Peptide hemolytic activity analysis using visual data mining of similarity-based complex networks. [PDF]
Castillo-Mendieta K+7 more
europepmc +1 more source
Neural Network Adaptive Control With Long Short‐Term Memory
ABSTRACT In this study, we propose a novel adaptive control architecture that provides dramatically better transient response performance compared to conventional adaptive control methods. This is accomplished by the synergistic employment of a traditional adaptive neural network (ANN) controller and a long short‐term memory (LSTM) network.
Emirhan Inanc+4 more
wiley +1 more source
Unlocking ensemble ecosystem modelling for large and complex networks. [PDF]
Vollert SA, Drovandi C, Adams MP.
europepmc +1 more source