COMPUTATIONAL ANALYSIS BY ARTIFICIAL INTELLIGENCE OF THE FRACTIONAL-ORDER PLANT VIRUS SPREAD MODEL

Viruses are an enormous threat to plants, humans, and animals, and they can have serious adverse impacts on the environment and economy. Plant viruses have the same destructive influence over ecological systems and crops as their counterparts in different species. Vectors, such as insects or other living things that help as transporters, are many ways for these certain plant viruses to spread. There is a time when a plant gets an infection from an infected individual when the virus circulates and grows in the plant’s tissues. The gap between the transmission of the virus and the start of symptoms permits its spread and enlargement, improving the possible damage to the plant host. We present a unique viewpoint on studying the dynamics of the plant virus spread (PVS) model by consuming a sustainability framework to estimate the environmental influence of viruses on the potato plant, by interchanging the integer order by a fractal fractional operator. The fractional-order PVS model is designed to epitomize the complex activities of the model perfectly as process innovation. The existence and unique results of the fractional order PVS model are cautiously observed by Lipschitz conditions. Additionally, within the fractional order context, we prudently prove the positivity and boundedness of the model. Likewise, Hyers–Ulam stability was used for the stability analysis. Furthermore, a numerical system was assembled for the fractional order PVS model. Ultimately, the numerical scheme Lagrangian interpolation is utilized to observe complex scenarios between viruses and plants.