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 …

This study presents a systematic framework to develop data-driven models for phosphorus
concentration in a full-scale wastewater treatment plant (WWTP). The dynamics of …

Data-driven soft sensor technology has been widely developed to estimate quality-related
variables, while following difficulties still limit its application in batch processes, such as …

As a high efficiency and environmental friendly energy conversion technique, proton
exchange membrane fuel cell (PEMFC) system faces challenges of limited durability and …

A sequencing batch reactor was modeled using multi-layer perceptron and radial basis
function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent …

In wastewater treatment process (WWTP), the accurate and real-time monitoring values of
key variables are crucial for the operational strategies. However, most of the existing …

Oxidation-reduction potential (ORP) sensors would constitute a robust surveillance and
control solution for aeration and external carbon dosing in wastewater biological treatment …

Wastewater treatment started off as a simple process to deal with the ecological impact of
human excretion and evolved to complex systems to deal with wastewater generated from …

When a sigmoidal feedforward neural network (SFNN) is trained by the gradient-based
algorithms, the quality of the overall learning process strongly depends on the initial weights …

The relationship between microbial community structure and function has been examined in
detail in natural and engineered environments, but little work has been done on using …