Optimizing Hyperparameter Values for Multi-Hidden Layer Extreme Learning Machine in Diagnosing Lumpy Skin Disease

Industry as illustrated by the 2020 India outbreak which aftermath saw more than ninety-seven thousand animal mortalities. The coping strategies assessed in this study are the diagnosis made using artificial intelligence (AI) which is important for early interventions. Response to LSD outbreaks is very relevant in order to keep the livestock sector responding favorably and to save on costs. MH-ELM and INV-ResNet-v2 were used for feature extraction for diagnosing LSD in calves with a success rate of 0.968. This increases the diagnostic capacity and virtually speeds up the time for the test and biopsy. This study shows how, through the use of advanced learning techniques, disease management could significantly benefit from the application of AI hence improving on response to diseases affecting agricultural production.