Combined adaptive <scp>neuro‐fuzzy</scp> inference system and genetic algorithm for e‐learning resilience assessment during <scp>COVID</scp> ‐19 pandemic

Given the growing use of e-learning and expansion internet-based infrastructure during COVID-19 epidemic, need for a resilient approach to systems is deeply felt. This article introduces combined technique utilizing adaptive neuro-fuzzy inference system (ANFIS) genetic algorithm (GA), named ANFIS-GA, evaluate resilience. In proposed ANFIS model, 22 features from five main factors including individual, technology, content, agility, assessment/support are used as fuzzy inputs, while resilience considered single output model. To select most significant evaluation resilience, an evolutionary feature selection based on GA used. The ANFIS-GA model has been successfully developed in virtual Iranian university. According obtained results, agility important factor, then, technology have next priorities Statistical analysis demonstrated that there no difference between experts' opinion via can be any educational institution improvement e-learning.