A novel hyperbolic time-delayed grey model with Grasshopper Optimization Algorithm and its applications

Discharge for wastewater treatment plays a key role in improving the water quality, thereby guaranteeing living quality of citizens. With high-speed economics growth and economics reforming, total amount of China's discharge of wastewater treatment is sharing high uncertainty, leading to many difficulties in accurate forecasts of discharge of wastewater treatment. Based on grey system theory, the hyperbolic time-delayed term is introduced in this paper to develop a novel forecasting model in order to deal with uncertainties of China's sewage discharge forecasting. The key nonlinear parameter of the proposed model is determined by the Grasshopper Optimization Algorithm. A series of practical numerical cases prove that the proposed model is reliable in comparison with six existing models are used for comparison. Then we apply it to predict the behavior of sewage discharge in China, those results against demonstrating the model our proposed has more satisfactory prediction precision. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-ncnd/4.0/).

Automated summary

The paper proposes a forecasting model based on grey system theory to address the uncertainties in predicting China's wastewater treatment discharge, introducing a hyperbolic time-delayed term and determining the key nonlinear parameter using the Grasshopper Optimization Algorithm. Through practical numerical cases, the proposed model demonstrates higher reliability and accuracy compared to existing models.