For combustion processes, it is important to monitor gases such as NO, in exhaust streams.
Traditional approaches for such emission monitoring use analytical instruments, which are …

Inferential or soft sensing techniques have been gaining momentum recently as viable
alternatives to hardware sensors in various situations, eg continuous emission monitoring …

Soft sensing or inferential estimation has long been considered a potent tool to deal with the
conflict between small control interval and large sampling interval existing in a wide variety …

Inferential sensing, or soft sensing, gained popularity in recent years as an alternative to
continuous emission monitoring systems because of its simplicity, reliability, and cost …

In this paper we compare a number of strategies to cope with the problem of small data sets
in the identification of a nonlinear process. Four methods are analyzed: expansion of the …

Soft sensors are essentially on-line models that provide an estimate of a desired process
variable that is not easily measured directly, on the basis of other process variables that are …

This work deals with the design and implementation of soft sensors for a Sulfur Recovery
Unit (SRU) in a refinery. Soft sensors are mathematical models able to emulate the behavior …

In this paper, algorithm of pattern extraction (Alopex) is introduced into the particle swarm
optimization (PSO) to train the artificial neural network (ANN), which is used to construct the …

This paper presents a multivariate data fusion procedure for design of dynamic soft sensors
where suitably selected image features are combined with traditional process …

The field of soft sensor development has gained significant importance in the recent past
with the development of efficient and easily employable computational tools for this purpose …