J.L. Pleumeekers, T. Mercier, F. Clérot and S. Mottet
For the design and optimisation of modern quantum well based opto‐electronic devices, a numerical simulator is required. This paper describes such a simulator. It includes the…
Abstract
For the design and optimisation of modern quantum well based opto‐electronic devices, a numerical simulator is required. This paper describes such a simulator. It includes the carrier transport through the quantum wells as well as the optical gain and the propagation of a light flux. This simulator is then used for the simulation of multi quantum well semiconductor optical amplifiers.
Sergei O. Kuznetsov, Alexey Masyutin and Aleksandr Ageev
The purpose of this study is to show that closure-based classification and regression models provide both high accuracy and interpretability.
Abstract
Purpose
The purpose of this study is to show that closure-based classification and regression models provide both high accuracy and interpretability.
Design/methodology/approach
Pattern structures allow one to approach the knowledge extraction problem in case of partially ordered descriptions. They provide a way to apply techniques based on closed descriptions to non-binary data. To provide scalability of the approach, the author introduced a lazy (query-based) classification algorithm.
Findings
The experiments support the hypothesis that closure-based classification and regression allow one to both achieve higher accuracy in scoring models as compared to results obtained with classical banking models and retain interpretability of model results, whereas black-box methods grant better accuracy for the cost of losing interpretability.
Originality/value
This is an original research showing the advantage of closure-based classification and regression models in the banking sphere.