In rail transit systems, improving transportation efficiency has become a research hotspot. In
recent years, a new method of train control system based on virtual coupling has attracted …

To address the issue of soft-sensing of effluent total phosphorus in wastewater treatment
processes (WWTPs), a soft-sensing system based on an adaptive recursive fuzzy neural …

To enhance the model's flexibility, this study proposes a self-organizing fuzzy neural network
(SOFNN) modeling methodology based on an adaptive quantum particle swarm …

In this paper, a novel self-organizing fuzzy neural network with an adaptive learning
algorithm (SOFNN-ALA) for nonlinear system modeling and identification in industrial …

On-line measuring of ammonia nitrogen in seawater is essential to the intensive aquaculture
process. Its concentration has an important effect on the growth and development of the …

An adaptive control algorithm based on the RBF neural network (RBFNN) and nonlinear
model predictive control (NMPC) is discussed for underwater vehicle trajectory tracking …

The Echo-State Network (ESN) is a robust recurrent neural network and a generalized form
of classical neural networks in time-series model designs. ESN inherits a simple approach …

Aiming at the control problem of nonlinear dynamic systems, a model predictive control
(MPC) method based on adaptive fuzzy neural network (AFNN) was proposed. First, in the …

Aiming at overlap and fuzziness between fault boundaries, faults, and characteristics under
load disturbances and measurement noise influence when the inverter is in an open‑circuit …

An improved fuzzy neural network model predictive control (MPC) method based on
dynamic partial least squares (DPLS) framework is proposed for the control of highly …