Nonlinear process modeling using multiple neural network (MNN) combination based on modified Dempster-Shafer (DS) approach

In this work, modified Demspter-Shafer (DS) is employed as the method for multiple neural networks (MNN) combination. The modified DS - MNN combination was employed to a nonlinear process. The `best´ single network condition is somehow a difficult condition to achieve especially in nonlinear process modeling; therefore, multiple neural networks were applied in this work. Furthermore, MNN was combined with a nonlinear combination method - DS method to further improved the MNN model. In this case, a conical water tank was used as the nonlinear system. Based on the results, the modified DS - MNN implementation in the nonlinear conic water tank system was convincing and showed the reliability of MNN as a modeling tool.