Abstract While feature selection helps to get smaller and more understandable prediction models, most existing feature-selection techniques do not consider domain knowledge. One way use knowledge is via constraints on sets of selected features. However, the impact constraints, e.g., predictive quality features, currently unclear. This article an empirical study that evaluates propositional arit...

The dogleg severity is one of the most important parameters in directional drilling. Improvement of these indicators actually means choosing the best conditions for the directional drilling in order to reach the target point. Selection of high levels of the dogleg severity actually means minimizing well trajectory, but on the other hand, increases fatigue in drill string, increases torque and d...

Different constraint handling techniques have been used with multiobjective evolutionary algorithms (MOEA) to solve constrained multiobjective optimization problems. It is impossible for a single constraint handling technique to outperform all other constraint handling techniques always on every problem irrespective of the exhaustiveness of parameter tuning. To overcome this selection problem, ...

Developing effective selection programs for improving the performance of livestock requires taking the economical selection indices into account. The present study was performed for comparing four selection indices developed in Kermani sheep through simulated data. The relative importance of traits was determined based on the estimated economic values and consequently, the most beneficial trait...