Hybrid Whale and Gray Wolf Deep Learning Optimization Algorithm for Prediction of Alzheimer’s Disease

In recent years, finding the optimal solution for image segmentation has become more important in many applications. The whale optimization algorithm (WOA) is a metaheuristic technique that advantage of achieving global while also being simple to implement and solving real-time problems. If complexity problem increases, WOA may stick local optima rather than optima. This could be an issue obtaining better solution. For this reason, paper recommends hybrid based on mixture gray wolf (GWO) segmenting brain sub regions, such as matter (GM), white (WM), ventricle, corpus callosum (CC), hippocampus (HC). consists two steps, i.e., GWO. proposed method helps diagnosing Alzheimer’s disease (AD) by regions (SRs) using GWO (H-WOA-GWO, which represented HWGO). segmented region was validated with different measures, it shows accuracy results 92%. Following segmentation, deep learning classifier utilized categorize normal AD images. combination yields 90%. As result, discovered suggested highly successful identifying ideal solution, paired classification.