Abstract Interest in Machine Learning applications to tackle clinical and biological problems
is increasing. This is driven by promising results reported in many research papers, the …

The estimation of sediment yield concentration is crucial for the development of stream
ventures, watershed management, toxins estimation, soil disintegration, floods, and so on. In …

A hybrid neural network‐first principles modeling scheme is developed and used to model a
fedbatch bioreactor. The hybrid model combines a partial first principles model, which …

This book discusses machine learning algorithms, such as artificial neural networks of
different architectures, statistical learning theory, and Support Vector Machines used for the …

We discuss a number of methods for estimating the standard error of predicted values from a
multilayer perceptron. These methods include the delta method based on the Hessian …

To use machine learning in high stakes applications (eg medicine), we need tools for
building confidence in the system and evaluating whether it is reliable. Methods to improve …

A Wave‐Net is an artificial neural network with one hidden layer of nodes, whose basis
functions are drawn from a family of orthonormal wavelets. The good localization …

Using radial basis functions to approximate a function and its error bounds | IEEE Journals &
Magazine | IEEE Xplore Using radial basis functions to approximate a function and its error …

We consider the problem of accuracy in heat rate estimations from artificial neural network
(ANN) models of heat exchangers used for refrigeration applications. Limited experimental …

The purpose of this review is three-fold. First, sketch the directions that research and
industrial applications of “intelligent systems” have taken in several areas of process …