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An effectivity tree is a new concept which we introduce to show how it can be used in applications related to uncertainty quantification of the widely varying information that typical plagues many complex problems. Modeling of effectivity trees can be thought of as an inverse process to the...
This paper proposes an unsupervised analysis methodfor identifying critical samples in large populations. The objective is to identify data features which help to pinpoint the critical samples that require the most inspection resources, namely time and money. Typically the data available for...
In this paper, a model-free approach for data mining in engineering is presented. The numerical approach is based on artificial neural networks. Recurrent neural networks for fuzzy data are developed to identify and predict complex dependencies from uncertain data. Uncertain structural processes...
Existence of heterogeneous results for a particular measurement is a typical problem in engineering sciences. This phenomenon represents data uncertainty. It means that a precise specification of a measurement is not possible. Only a non-stochastic dataset is available. In this paper, a new...
Commercially available hand prostheses are controlled by myoelectric signals, biosignals that must be accurately interpreted if a prosthesis is to work effectively. We propose the use of standardized muscle contractions to select grasp types; these are taught to the prosthesis using data mining...
Equipment condition monitoring of nuclear power plants requires to optimally group the usually very large number of signals and to develop for each identified group a separate condition monitoring model. In this paper we propose an approach to optimally group the signals. We use a Genetic...
Network intrusion detectors analyze network traffic for detecting attacks in computer networks. Achieving a high detection accuracy and in particular a low number of false alarms is crucial for their practical use. In this paper a new stacking approach is suggested for improving the detection...
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