In diesem Beitrag werden die Grundzüge des industriellen Lernens vorgestellt und gezeigt, welche Strategien sich aus der Kenntnis von Lerneffekten ableiten lassen. Die lernfähige Produktion nutzt diese Ansätze in allen Bereichen aus, um Wettbewerbsvorteile durch höhere Lerngeschwindigkeiten zu erzielen. Da in der diskontinuierlichen Produktion sehr...
This paper describes the hybrid algorithm DIPOL-DT which uses the strengths of standard decision tree algorithms and piecewise linear classifiers because at every level of learning it chooses the appropriate subdivision of the attribute space: a split with hyperplanes in general position or an axis-parallel split. The proposed method combines two e...
This paper outlines an approach for generating a series of optimal control actions in processes, which cannot (or can only partly) be modelled mathematically, by combining learning with problem solving methods. This approach has a suitable real time behaviour and can handle a larger number of different discrete control actions. A training data set ...
An algorithm for learning decision trees for classification and prediction is described which converts realvalued attributes into intervals using statistical considerations. The trees are automatically pruned with the help of a threshold for the estimated class probabilities in an interval. By means of this threshold the user can control the comple...
This paper presents a learning algorithm which constructs an optimised piecewise linear classifier for nclass problems. In the first step of the algorithm initial positions of the discriminating hyperplanes are determined by linear regression for each pair of classes. To optimise these positions depending on the misclassified patterns an error crit...
