Artificial Neural NetworksAvailable Parameter PickingPattern BuildingPattern CheckingThis chapter is dedicated to the scope of which facts should be considered when deciding whether a Neural Network (NN) solution is suitable to solve a given problem. This is followed by a detailed example of a ...
Neural networks are usually trained using the output errors of the network, instead of using the output errors of the controlled plant. However, when a neural network is used to control a plant directly, the output errors of the network are unknown, since the desired control actions are ...
Artificial neural networks show potential for modeling the behavior of complex nonlinear processes, such as those involved in the occurrence of breakup ice jams. Because breakup ice jams and related flooding occur suddenly, ice jam prediction methods are desirable to provide early warning and to allow...
The algorithm Triatlon for neural network cluster analysis was applied in the personality study of 666 male subjects, 18 years old, randomly selected from the population of clinically healthy and literate young males. The sample was described over a set of eleven personality variables selected under...
Summary: This paper describe an application of a neural network approach to SM (standard model) and MSSM (minimal supersymetry standard model) Higgs search in the associated production $ t\\overline{t} H$ with $H ightarrow b\\overline{b}$. This decay channel is considered as a discovery ...
In the field of tribology, many studies now use machine learning (ML). However, ML models have not yet been used to evaluate the relationship between the friction coefficient and the elemental distribution of a tribofilm formed from multiple lubricant ad
Introduction The so called Kohonen Feature Map (KFM) is a type of Neural Network, which – after a phase of training – is able to recognize complex information structures, which are called patterns. In terms of sport such patterns e.g. can be processes or situations/states in games or mo...
Application of Neural Networks for Predicting Partition Coefficient Based on Atom-Type Electrotopological State Indices. The aim of this study was to determine the efficacy of atom-type electrotopological state indices for estimation of the octanol-water partition coefficient... JJ Huuskonen,A Villa,...
The learning method of layered neural networks can be supervised or unsupervised. Back propagation learning algorithm is a common method of supervised learning that can learn automatically from teaching patterns. However, accurate teaching patterns are not always available for robotic applications and it ...
Application of neural networks technique for acoustic emission NDT method (In French, English abstract) : Cherfaoui, M. 6th European Conference on Non Destructive Testing, Nice (France), 24–28 Oct. 1994. Vol. 1. pp. 489–491. ECNDT (1994)Show moreShow less...