Innovative storage technology and the rising popularity of the Internet have generated an
ever-growing amount of data. In this vast amount of data much valuable knowledge is …

Support vector machines (SVMs) are currently state-of-the-art for the classification task and,
generally speaking, exhibit good predictive performance due to their ability to model …

In this paper, we present a recursive algorithm for extracting classification rules from
feedforward neural networks (NNs) that have been trained on data sets having both discrete …

This paper addresses the endemic problem of the gap between predicted and actual energy
performance in public buildings. A system engineering approach is used to characterize …

An important drawback of many artificial neural networks (ANN) is their lack of explanation
capability [Andrews, R., Diederich, J., & Tickle, AB (1996). A survey and critique of …

Compelling evidence indicates the existence of bidirectional communication between
astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive …

Whereas newer machine learning techniques, like artificial neural networks and support
vector machines, have shown superior performance in various benchmarking studies, the …

Many of the state-of-the-art data mining techniques introduce nonlinearities in their models
to cope with complex data relationships effectively. Although such techniques are …

An application of genetic programming (GP) and artificial neural networks (ANNs) in
hydrology is proposed, showing how these two techniques can work together to solve the …

The importance of astrocytes, one part of the glial system, for information processing in the
brain has recently been demonstrated. Regarding information processing in multilayer …