Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/2950 2018 2018 Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura 35111, Egypt Ahmed Ahmed Department of Electronics and Communications Engineering, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt Mohamed G. Abdelfattah Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura 35111, Egypt; MEU Research Unit, Middle East University, Amman 11831, Jordan El-Sayed M. El El-Kenawy Department of Electronics and Communications Engineering, Faculty of Engineering, Mansoura University, Egypt Hossam El-Din Moustafa After the COVID-19 epidemic, public health awareness increased. A skin viral disease known as monkeypox sparked an emergency alert, leading to numerous reports of infections across numerous European countries. Common symptoms of this disease are fever, high temperatures, and water-filled blisters. This paper presents one of the recent algorithms based on a metaheuristic framework. To improve the performance of monkeypox classification, we introduce the GGO algorithm. Firstly, we employ four pre-trained models (AlexNet, GoogleNet, Resnet-50, and VGG-19) to extract the most common features of monkeypox skin image disease (MSID). Then, we reduce the number of extracted features to select the most distinguishing features for the disease. We make it by using GGO in binary form, which has an average fitness of 0.60068 and a best fitness of 0.50248. Lastly, we apply various optimization algorithms, including the (WWPA) waterwheel plant algorithm, the (DTO) Boosted Dipper Throated Optimization, the (PSO) particle swarm optimizer, the (WAO) whale optimization algorithm, the (GWO) gray wolf optimizer, the (FA) firefly algorithm, and the GGO algorithm, all based on the Convolution Neural Network (CNN), to achieve the best performance. Best Performance is indicated in accuracy and sensitivity; it reached 0.9919 and 0.9895 by GGO. A rigorous statistical analysis test was applied to confirm the validity of our findings. We applied Analysis of Variance ANOVA, and Wilcoxon signed tests, and the results indicated that the value of p was less than 0.005, which strongly supports our hypothesis.   2024 2024 86 107 10.54216/FPA.160206 https://www.americaspg.com/articleinfo/3/show/2950