A. J. M. M. Weijters (original) (raw)

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Papers by A. J. M. M. Weijters

Systems Research and Behavioral Science, 2002

Batch processing is becoming more important in the process industries, because of the increasing ... more Batch processing is becoming more important in the process industries, because of the increasing product variety and the decreasing demand volumes for individual products. In batch process industries it is difficult to estimate the completion time, or makespan, of a set of jobs, because jobs interact at the shop floor. We assume a situation with hierarchical production control consisting of

The deployment of Worko w Management systems is a time- consuming and error-prone task. A possibl... more The deployment of Worko w Management systems is a time- consuming and error-prone task. A possible solution is process min- ing, which automatically extracts worko w models from event-data logs. However, the current research in process mining still has problems in mining some common constructs in worko w models. Among these con- structs are short loops, which are loops of

Neural Processing Letters, 1995

For some problems, the back-propagation learning rule often used for training multilayer feedforw... more For some problems, the back-propagation learning rule often used for training multilayer feedforward networks appears to have serious limitations. In this paper we describe BP-SOM, an alternative training procedure. In BP-SOM the traditional back-propagation learning rule is combined with unsupervised learning in self-organizing maps. While the multilayer feedforward network is trained, the hidden-unit activations of the feedforward network are used

European Journal of Operational Research, 2003

Reactivity of Solids, 2007

Although there has been a lot of progress in developing pro- cess mining algorithms in recent yea... more Although there has been a lot of progress in developing pro- cess mining algorithms in recent years, no eort has been put in devel- oping a common means of assessing the quality of the models discovered by these algorithms. In this paper, we outline elements of an evaluation framework that is intended to enable (a) process mining researchers to compare