Biomedical subjects

Jining Chen

Publications and source records attributed to Jining Chen.

6 recordsLinked to original sources

PubMed2004

Wastewater reuse potential analysis: implications for China's water resources management.

It has been recognized that wastewater reuse or reclamation serves as an efficient and valuable way to cope with the scarcity of water resources and severity of water pollution. This paper presents the systematic framework of wastewater reuse potential estimation. Based on the regional disparities in China, a linear programming optimization model is developed to explore the potential wastewater reuse quantities, under physical and economic constraints. Sensitivity analysis and Robust Counterpart (RC) optimization are performed to discuss the influences of key parameters and the reuse quantity's decision making under uncertainty. Based on the model, effectiveness of different policy scenarios of water price changes are simulated and evaluated, providing information regarding China's water and wastewater management.

China↗

PubMed2003

[Comparison of optimum, RSA and GLUE methods in parameter identification of a nonlinear environmental model].

Parameter identification plays a key role in environmental model application. The optimization method is one of the earliest and most widely used methods. However, as the parameters by optimization may not fully fit the observations, there is a risk that the errors may be enhanced in the decision-make stage. With this deficiency in consideration, the RSA and GLUE algorithms search for the feasible parameters not only to the optimum but also around the neighbors. The difference between RSA and GLUE is that the RSA accepts the estimated parameters equally as the candidates for application; while the GLUE keeps the difference among the parameters as measured by likelihood. In addition for parameter identification, both RSA and GLUE are efficient tools for global sensitivity analysis.

Environment↗

PubMed2002

[Comparison of parameter optimization algorithms for environmental model].

Parameters identification is achieved through the minimization of objective function based on model outputs and the observed data. Because of ever increasing complexity of environmental-models, there are significant difficulty for conventional optimal methods to present a global optimization. On the contrast, however, direct optimization algorithms are widely developed in recent years due to increasing computer efficiency and show promising applications. Four direct optimal algorithms, i.e. CRS algorithm, SCE UA algorithm, SA algorithm and Annealing-Simplex algorithm, were thus selected in this paper to compare their performances via case studies.

Algorithms↗

PubMed2002

[A study on non-point source pollution models].

With the effective control of industrial wastewater, pollution of non-point sources has become increasingly important in China. The understanding of non-point source pollution processes, mostly through mathematical models, is thus a prior knowledge to its effective control. A review is presented in this paper, regarding the development of non-point source pollution models. The conceptualization, structure and major processes of non-point source models are systematically summarized and several widely applied models are compared so as to assess its state of art. The future development trends of non-point source model are also discussed.

Industrial Waste↗

PubMed2002

[Future scale and market capacity of urban water environmental infrastructure in China: a system dynamic model].

With the application of system dynamics, a dynamic, nonlinear model (SDMUWEIC) was developed in this paper in order to reflect the relationships of population, economic, resources and environment. Through a systematic procedure of model validation and uncertainty analysis, the model was applied for predicting and analyzing the future market capacity and constituents of urban water infrastructure. It illustrated the volumes and trends of potential capital market in construction, general mechanical equipments and water treatment instruments as well as their relevant influencing factors including water pricing and urbanization rate. Several different scenarios were further under test to reveal the sensitivity of different uncertain components.

Environment↗

PubMed2002

[Parameters identification and uncertainty analysis for environmental model].

This paper examined a case study of hydrological model for identifying parameter uncertainty by using three sensitivity analysis methods: HSY algorithm, linear regressional method and coupling analysis method. The results showed that optimal algorithms cannot give a sound explanation for complexity of model structure and identifying model parameters via uncertainty analysis methods presented an effective alternative to understand model system.

Algorithms↗