With the predicted depletion of natural resources and alarming environmental issues,
sustainable development has become a popular as well as a much-needed concept in …

Soft sensors for regression applications (SSR) are inferential models that use online
available sensors (eg temperature, pressure, flow rate, etc.) to predict quality variables …

In the last two decades Soft Sensors established themselves as a valuable alternative to the
traditional means for the acquisition of critical process variables, process monitoring and …

Text categorization is widely used when organizing documents in a digital form. Due to the
increasing number of documents in digital form, automated text categorization has become …

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In response to the exponentially increasing need to analyze vast amounts of data, Neural
Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern …

In this article, we review and discuss algorithms for adaptive data-driven soft sensing. In
order to be able to provide a comprehensive overview of the adaptation techniques …

The prediction of tropospheric ozone concentrations is very important due to the negative
impacts of ozone on human health, climate and vegetation. The development of models to …

Operation and maintenance constitute a substantial share of the lifecycle expenditures of an
offshore renewable energy farm. A noteworthy number of methods and techniques have …

In many industrial plants, development and implementation of advanced monitoring and
control techniques require real-time measurement of process quality variables. However, on …