A novel neural network integrating conjugate gradient comparison and Support Vector Machine will do this. Materials and Procedures: If 5G networks with several tenants can enhance their forecasts by using Support Vector Machines and neural network conjugate gradient comparison, then. each of the two groups in this scenario had twenty people randomly allocated to them. A p-value of 0.001 and a G-power of 80% would be used to establish the intended sample size. A 90% success rate is achieved by the 5G network in instances with a single tenant; however, this lowers to an 85% success rate when there are several tenants. Using independent samples t-tests, a 2-tailed result of 0.001 (p < 0.05) demonstrates a substantial disparity in accuracy between the two methods. The one-of-a-kind neural network conjugate gradient statistically beats support vector machine.