Pneumonia detection using butterfly optimization and hybrid butterfly optimization algorithm

Pneumonia affects so many people around the world, which leads to of them being killed. In order identify and diagnose disease, patient must first undergo an x-ray scan chest (CXR). Disease will be identified according CXR images. Software diagnostic tools are used help decision-making promote pneumonia diagnosis process. From these is gray level distribution moments (GLDM) algorithm for image features extraction, we meta-heuristic representing basic butterfly optimization using lèvy flight (BOALF) modified (BOARN) detect on basis extracted features. And then we've also been making hybrid between BOA with fuzzy membership function get as novel method called it (FBOA). These methods were based various images chest. testing phase, proposed obtained highest rate disease compared other two in this work.