@conference {12880,
	title = {Problems encountered when determining the risk of an event in case of imprecise information.},
	booktitle = {Symposia on Methods of Artificial Intelligence},
	year = {2002},
	abstract = {<p>We consider the problem of predicting a risk index of an event on the base of several predictors. The specificity of the problem lies in the fact, that there are no training data; instead we have a set of logical rules describing in a fuzzy way several classes of the risk ({\textquoteright}very low{\textquoteright}, {\textquoteright}low{\textquoteright}, {\textquoteright}medium{\textquoteright}, {\textquoteright}high{\textquoteright} and {\textquoteright}very high{\textquoteright} risk). We present several problems and doubts we had met when trying to construct a predictor. After considering several alternatives we stated that a simple neural network architecture (with one perceptron) calculating logistic regression has given the best agreement with expert opinion. Thus,<br>based on the rules, we are able to mimic the expert opinion by a neural network model.</p>},
	author = {Bartkowiak, A. and Evelpidou, N. and Vassilopoulos, A.}
}
