Water pollution estimation based on the 2D transport–diffusion model and the Singular Evolutive Interpolated Kalman filter

2014 ◽  
Vol 342 (2) ◽  
pp. 106-124 ◽  
Author(s):  
Thu Ha Tran ◽  
Dinh Tuan Pham ◽  
Van Lai Hoang ◽  
Hong Phong Nguyen
Keyword(s):  
Water Pollution ◽  
Kalman Filter ◽  
Diffusion Model ◽  
Transport Diffusion

Study of water pollution through a Lévy flight jump diffusion model with stochastic jumps of pollutants

2019 ◽  
Vol 33 (19) ◽  
pp. 1950210 ◽  
Author(s):  
Mohamed Abd Allah El-Hadidy
Keyword(s):  
Water Pollution ◽  
Diffusion Model ◽  
Waiting Time ◽  
Gaussian Distribution ◽  
Jump Diffusion ◽  
Lévy Flight ◽  
Large Area ◽  
Levy Flight ◽  
Jump Distance ◽  
Jump Diffusion Model

In this paper, we present the multivariate distribution of independent Lévy flight jump diffusion molecules that cause water pollution. We consider that the waiting time of this jump has a Gaussian distribution. Rather than studying the statistical properties of this distribution in water, we estimate the length of the jump distance parameters for each molecule. These estimated jump distances of the molecules are used to predict the proportion of pollution in a large area of the sea.

scholarly journals A Study on Water Pollution Source Localization in Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Jun Yang ◽  
Xu Luo
Keyword(s):  
Water Pollution ◽  
Diffusion Model ◽  
Source Localization ◽  
Pollution Source ◽  
Good Choice ◽  
Diffusion Models ◽  
Hypotheses Testing ◽  
Localization Algorithm ◽  
Source Detection ◽  
Localization Method

The water pollution source localization is of great significance to water environment protection. In this paper, a study on water pollution source localization is presented. Firstly, the source detection is discussed. Then, the coarse localization methods and the localization methods based on diffusion models are introduced and analyzed, respectively. In addition, the localization method based on the contour is proposed. The detection and localization methods are compared in experiments finally. The results show that the detection method using hypotheses testing is more stable. The performance of the coarse localization algorithm depends on the nodes density. The localization based on the diffusion model can yield precise localization results; however, the results are not stable. The localization method based on the contour is better than the other two localization methods when the concentration contours are axisymmetric. Thus, in the water pollution source localization, the detection using hypotheses testing is more preferable in the source detection step. If concentration contours are axisymmetric, the localization method based on the contour is the first option. And, in case the nodes are dense and there is no explicit diffusion model, the coarse localization algorithm can be used, or else the localization based on diffusion models is a good choice.

Two-stage cubature Kalman filter and its application in water pollution modeling

2019 ◽  
Vol 151 ◽  
pp. 332-341
Author(s):  
Lu Zhang ◽  
Yongfei Miao ◽  
Hailun Wang ◽  
Jianwen Fang
Keyword(s):  
Water Pollution ◽  
Kalman Filter ◽  
Two Stage ◽  
Cubature Kalman Filter ◽  
Pollution Modeling
Sign in / Sign up

Export Citation Format

Share Document