Anzeige
Erschienen in:
2011 | OriginalPaper | Buchkapitel
An Automatic Evolution of Rules to Identify Students’ Multiple Intelligence
verfasst von : Kunjal Mankad, Priti Srinivas Sajja, Rajendra Akerkar
Erschienen in: Advanced Computing
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The proposed work focuses on Genetic-Fuzzy approach to identify student’s skills. It is an integrated approach of education and technology implementing Theory of Multiple Intelligence. The objective is to reduce the system’s developmental and maintenance effort and automatically evolve strong rules. The proposed model is a novel evolutionary hybrid approach to measure and classify multiple intelligence in a friendly way. The paper includes general architecture of the model with front end and back end designs including encoding strategy, fitness function, crossover operator, and sample evolved rules and results. It concludes with the scope and application of the work to other domains.