Advances in artificial neural networks, machine learning and computational intelligence

Advances in artificial neural networks, machine learning and computational intelligence

This special issue of Neurocomputing presents N original articles, which are extended versions of selected papers from the 21 European Symposium on Artificial Neural Networks (ESANN). ESANN is a single-track conference held annually in Bruges, Belgium, one of the most beautiful medieval towns in Europe, whose atmosphere favours efficient work as well as enjoyable cultural activities (Bruges is ...

Computational Learning Theory for Artificial Neural Networks

There are many types of activity which are commonly known as ‘learning’. Here, we shall discuss a mathematical model of one such process, known as the the ‘probably approximately correct’ (or PAC) model. We shall illustrate how key problems of learning in artificial neural networks can be studied within this framework, presenting theoretical analyses of two important issues: the size of trainin...

Advances in computational intelligence and learning

Machine Learning for Wireless Networks with Artificial Intelligence: A Tutorial on Neural Networks

Next-generation wireless networks must support ultra-reliable, low-latency communication and intelligently manage a massive number of Internet of Things (IoT) devices in real-time, within a highly dynamic environment. This need for stringent communication quality-of-service (QoS) requirements as well as mobile edge and core intelligence can only be realized by integrating fundamental notions of...

Neural Networks and Artificial Intelligence

SYNOPSIS Assessment of surgical risk in patients undergoing pulmonary resection is a fundamental goal for thoracic surgeons. Usually used risk scores do not predict the individual outcome. Data Mining (DM) and Artificial Neural Networks (ANN) are artificial intelligence mathematical models that have been used for estimation of several prognostic situations. When used to assess surgical risk the...