In fuzzy rule-based classification systems, rule weight has often been used to improve the classification accuracy. In past research, a number of heuristic methods for rule weight specification have been proposed. In this paper, a method of fuzzy rule weight specification using Receiver Operating Characteristic (ROC) analysis is proposed. In order to specify the weight of a fuzzy rule, using 2-...

We address the problem of scheduling a multiclass M/M/m queue with Bernoulli feedback on m parallel servers to minimize time-average linear holding costs. We analyze the performance of a heuristic priority-index rule, which extends Klimov’s optimal solution to the singleserver case: servers select preemptively customers with larger Klimov indices. We present closed-form suboptimality bounds (ap...

When people judge the time that can be saved by increasing the speed of an activity, they are often victims of a time saving bias. That is, they overestimate the time that can be saved by increasing the speed. Judgments of time savings following speed increase when driving follow the Proportion heuristic [Svenson, O. (1970). A functional measurement approach to intuitive estimation as exemplifi...

Dynamic scheduling of manufacturing systems has primarily involved the use of dispatching rules. In the context of conventional job shops, the relative performance of these rules has been found to depend upon the system attributes, and no single rule is dominant across all possible scenarios. This indicates the need for developing a scheduling approach which adopts a state-dependent dispatching...

The so-called sum rule for the extinction cross section has been the subject of several publications. However, it has not been obtained directly from the macroscopic Maxwell equations but rather follows from heuristic causality considerations. It is argued that these causality considerations are, in fact, questionable and do not follow from the fundamental concept of electromagnetic scattering ...

Data Mining techniques are useful for analyzing data from many different dimensions and for identifying relationships. Non-parametric data models are explored and a heuristic approach is proposed for specific rule generation in practical cases. The most suited algorithm for a specific application is presented and learning methods evaluation is given. A problem of feature extraction and specific...

The rule labeling heuristic aims to establish confluence of (left-)linear term rewrite systems via decreasing diagrams. We present a formalization of a confluence criterion based on the interplay of relative termination and the rule labeling in the theorem prover Isabelle. Moreover, we report on the integration of this result into the certifier CeTA, facilitating the checking of confluence cert...

Making accurate judgments is a core human competence and a prerequisite for success in many areas of life. Plenty of evidence exists that people can employ different judgment strategies to solve identical judgment problems. In categorization, it has been demonstrated that similarity-based and rule-based strategies are associated with activity in different brain regions. Building on this researc...

The condensed nearest neighbor (CNN) algorithm is a heuristic for reducing the number of prototypical points stored by a nearest neighbor classifier, while keeping the classification rule given by the reduced prototypical set consistent with the full set. I present an upper bound on the number of prototypical points accumulated by CNN. The bound originates in a bound on the number of times the ...