DOI: 10.36347/sjpms.2020.v07i09.002

Pages: 192-196

Logistic growth model, as an important mathematical model to describe population or population changes, is now widely used in many fields. Researchers found that the problems involved cover many disciplines such as mathematics, physics, medicine, and biology. Therefore, the Logistic growth model has a strong application background and practical significance. This paper improves the logistic growth model that introduces harvest items, and applies the improved model to population forecasting. And with the help of mathematical software and the principle of least squares method to estimate the parameters of the improved model, the curve fitting comparison verifies that the improved model can achieve better results.