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The work presented in this paper is part of the cooperative research project AUTO-OPT carried out by twelve partners from the automotive industries. One major work package concerns the application of data mining methods in the area of automotive design. Suitable methods for data preparation and data analysis are developed. The objective of the work is the re-use of data stored in the crash-simulation department at BMW in order to gain deeper insight into the interrelations between the geometric variations of the car during its design and its performance in crash testing. In this paper a method for data analysis of finite element models and results from crash simulation is proposed and application to recent data from the industrial partner BMW is demonstrated. All necessary steps from data pre-processing to re-integration into the working environment of the engineer are covered.
Longitudinal observational databases have become a recent interest in the post marketing drug surveillance community due to their ability of presenting a new perspective for detecting negative side effects. Algorithms mining longitudinal observation
Image of an entity can be defined as a structured and dynamic representation which can be extracted from the opinions of a group of users or population. Automatic extraction of such an image has certain importance in political science and sociology r
A lot of time is spent searching for the most performing data mining algorithms applied in clinical diagnosis. The study set out to identify the most performing predictive data mining algorithms applied in the diagnosis of Erythemato-squamous disease
Side effects of prescribed medications are a common occurrence. Electronic healthcare databases present the opportunity to identify new side effects efficiently but currently the methods are limited due to confounding (i.e. when an association betwee
Topological Data Analysis (TDA) is the collection of mathematical tools that capture the structure of shapes in data. Despite computational topology and computational geometry, the utilization of TDA in time series and signal processing is relatively