Uncertainty-based Gompertz growth model for tumor population and its numerical analysis

For treating cancer, tumor growth models have shown to be a valuable resource, whether they are used develop therapeutic methods paired with process control or simulate and evaluate treatment processes. In addition, fuzzy mathematical model is tool for monitoring the influences of various elements creating behavioral assessments. It has been designed decrease ambiguity parameters obtain reliable development by employing logic.The Gompertz equation in an imprecise environment this study. considers whole cancer cell population vague at any given time, possibility distribution function determined initial population, net rate, carrying capacity tumor. Moreover, work provides information on expected maximum period. This study examines modeling insights based fuzziness reduce uncertainty achieve degree realism. Finally, numerical simulations utilized show significant conclusions proposed