This paper surveys and discusses the application of data-derived soft-sensing techniques in
biological wastewater treatment plants. Emphasis is given to an extensive overview of the …

With the aid of neural networks, this article develops two data-driven designs of fault
detection (FD) for dynamic systems. The first neural network is constructed for generating …

In the Proportional-Integral-Derivative (PID) controllers the control signal is a linear function
of: the current control error (the proportional part), the past errors (the integral part) and the …

A novel chaotic time-series prediction method based on support vector machines (SVMs)
and echo-state mechanisms is proposed. The basic idea is replacing" kernel trick" with" …

An unappealing characteristic of all real-world systems is the fact that they are vulnerable to
faults, malfunctions and, more generally, unexpected modes of-haviour. This explains why …

Bus arrival time prediction intends to improve the level of the services provided by
transportation agencies. Intuitively, many stochastic factors affect the predictability of the …

Hurricanes constitute major natural disasters that lead to destruction and loss of lives.
Therefore, to reduce economic loss and to save human lives, an accurate forecast of …

Reliable and timely fault detection and isolation are necessary tasks to guarantee
continuous performance in complex industrial systems, avoiding failure propagation in the …

In this paper, a continuous time recurrent neural network (CTRNN) is developed to be used
in nonlinear model predictive control (NMPC) context. The neural network represented in a …

This paper presents an identification method of dynamic systems based on a group method
of data handling approach. In particular, a new structure of the dynamic multi-input multi …