Water Quality Evolution Mechanism Modeling and Estimation Based on Fruit Fly Optimization Algorithm and Particle Filter

Abstract

Water Quality Evolution Mechanism (WQEM) modeling and Water quality estimation are important technical means for water pollution prevention and control of lakes and reservoirs. However, existing classical WQEM models usually contain unknown parameters with empirical values range, which brings difficulty of estimation water quality changes of specific lakes and reservoirs to meet the accuracy requirements. Furthermore, water quality indicator is susceptible to natural factors and human factors, which makes the water system complex and nonliner, and enhances the difficulty of water quality estimation. Therefore, combining water quality mechanism, this paper proposes a Fruit Fly Optimization Algorithm (FFOA) based WQEM modeling method and studies a method of water quality estimation based on Particle Filter (PF) algorithm. First, a more comprehensive WQEM model is established to characterize the water quality mechanism of lakes and reservoirs. Then, combining observed data of water quality indicator and WQEM, the unknown parameters of a WQEM model are estimated by using FFOA. Finally, PF algorithm is used to estimate the water quality status. Simulation results show that the method can effectively estimate the unknown parameters of the WQEM model and estimate the water quality status.