Retraction Note: Stability of river ecological bank slope based on network prediction model and monitoring of exercise weight loss effect

Abstract

In this paper, the BP neural network is optimized by using the network prediction algorithm to eliminate the shortcomings of the traditional BP neural network, such as local minimum and slow convergence speed, and the performance of the network prediction model is determined through comparative simulation experiments. Then, ABAQUS is used to create a numerical finite element model of river ecological bank slope, and its stability is analyzed by numerical simulation. The main factors considered are the change of water level in the canal, the influence of precipitation, and the influence of ship waves. On the basis of finite element analysis, combined with multilanguage programming method, we completed the construction of river ecosystem slope stability early warning platform based on GIS and finite element technology. Secondly, the shallow root reinforcement and deep root vegetation anchorage are determined to improve the stability of the bank slope, so as to better guide the design and application of riparian ecological protection projects. Finally, the network prediction model is used to monitor the effect of weight loss, then find the maximum fatty acid strength of overweight people, and make Fatmax weight loss plan for overweight people. In addition, we will compare the effect of Fatmax weight loss exercise program on various body functions of obese people in normal and hypoxic environments, so as to provide reference for those who are going to lose weight. In this paper, through the study of network prediction model and river ecological slope stability, it is applied to the research of sports weight loss effect monitoring, which promotes the better development of sports weight loss.