Application of Optimal Control and Fuzzy Theory for Dynamic Groundwater Remediation Design

Chu, Hsin; Chang, Liang-Cheng

doi:10.1007/s11269-008-9293-1

Cited by 37 publications

(11 citation statements)

References 22 publications

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“…ISOQUAD is a groundwater flow and contaminants transport simulation model for a confined two-dimensional aquifer (Pinder 1978). The transport model includes changes of contaminant concentration owing to advection, diffusion, dispersion, and the adsorption isotherm of aquifer (Chu and Chang 2009b). Numerical scheme applied in the model is the Galerkin finite element method for spatial integration and implicit finite difference for time integration.…”

Section: Integration Of Cddp and Annmentioning

confidence: 99%

“…To ensure sustainable groundwater use, administrators must employ remediation policies such as the pump-and-treat (P&T) method. The P&T method is primarily common and useful for decontaminating groundwater with highly soluble pollutants by pumping out and treating contaminated groundwater (Chu and Chang 2009b). Several studies have investigated the feasibility of coupling optimization technique with groundwater flow and transporting simulation to design P&T systems (Chang et al 1992;McKinney and Lin 1994;Wang and Zheng 1998;Chang and Hsiao 2002;Chu et al 2005;Chang et al 2007).…”

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confidence: 99%

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Integration of Optimal Dynamic Control and Neural Network for Groundwater Quality Management

Chang

Chu

Hsiao

2011

Water Resour Manage

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This study integrates an artificial neural network (ANN) and constrained differential dynamic programming (CDDP) to search for optimal solutions to a nonlinear time-varying groundwater remediation-planning problem. The proposed model (ANN-CDDP) determines optimal dynamic pumping schemes to minimize operating costs and meet water quality requirements. The model uses two embedded ANNs, including groundwater flow and contaminant transport models, as transition functions to predict groundwater levels and contaminant concentrations under time-varying pumping. Results demonstrate that ANN-CDDP is a simplified management model that requires considerably less computation time to solve a fine mesh problem. For example, the ANN-CDDP computing time for a case involving 364 nodes is 1/26.5 that of the conventional optimization model.

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Section: Integration Of Cddp and Annmentioning

confidence: 99%

mentioning

confidence: 99%

Integration of Optimal Dynamic Control and Neural Network for Groundwater Quality Management

Chang

Chu

Hsiao

2011

Water Resour Manage

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“…The fuzzy inference system (FIS) is an artificial intelligence technique that combines the fuzzy set, fuzzy logic, and fuzzy reasoning [1,[3][4][5][6]. The FIS utilizes linguistic variables, fuzzy rules, and fuzzy reasoning and provides a tool for knowledge representation based on degrees of membership [7]. During the past decade, the FIS application ranged from runoff forecasting to surface water supply [3-6, 8, 9].…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Inference System for the Conjunctive Use of Surface and Subsurface Water

Chang

Chu

Chen

2013

Advances in Fuzzy Systems

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This study develops the water resources management model for conjunctive use of surface and subsurface water using a fuzzy inference system (FIS). The study applies the FIS to allocate the demands of surface and subsurface water. Subsequently, water allocations in the surface water system are simulated by using linear programming techniques, and the responses of subsurface water system with respect to pumping are forecasted by using artificial neural networks. The operating rule for the water systems is that the more abundant water system supplies more water. By using the fuzzy rule, the FIS conjunctive use model easily incorporates expert knowledge and operational polices into water resources management. The result indicates that the FIS model is more effective and efficient when compared with the decoupled conjunctive use and simulation-optimization models. Furthermore, the FIS model is an alternative way to obtain the conjunctive use policies between surface and subsurface water.

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“…Fuzzy techniques are more suitable to express the possibilistic uncertainties, which are originated from incomplete or imprecise information (Kentel and Aral 2005). Previously, extensive studies in applying either group of methods were X. S. Qin (&) School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore e-mail: xsqin@ntu.edu.sg reported (Terracini 1996;Mylopoulos et al 1999;Chen 2000;Maqsood et al 2003;Kentel and Aral 2004;Mckone and Deshpande 2005;Kentel and Aral 2007;Li et al 2007;Qin et al 2008;Chu and Chang 2009;Gutiérrez et al 2009). In recent years, it has been demonstrated by many researchers that the integrated fuzzy stochastic methods are more useful in compensating the limitations of each group of methods and have a better applicability in addressing risk assessment problems involving different kinds of uncertainties (Ferson and Ginzburg 1996).…”

Section: Introductionmentioning

confidence: 99%

Assessing environmental risks through fuzzy parameterized probabilistic analysis

Qin

2011

Stoch Environ Res Risk Assess

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A fuzzy parameterized probabilistic analysis (FPPA) method was developed in this study to assess risks associated with environmental pollution-control problems. FPPA integrated environmental transport modeling, fuzzy transformation, probabilistic risk assessment, fuzzy risk quantification into a general risk assessment framework, and was capable of handling uncertainties expressed as fuzzy-parameterized stochastic distributions. The proposed method was applied to two environmental pollution problems, with one being about the point-source pollution in a river system with uncertain water quality parameters and the other being concerned with groundwater contaminant plume from waste landfill site with poorly known contaminant physical properties. The study results indicated that the complex uncertain features had significant impacts on modeling and risk-assessment outputs; the degree of impacts of modeling parameters were highly dependent on the level of imprecision of these parameters. The results also implied that FPPA was capable of addressing vagueness or imprecision associated with probabilistic risk evaluation, and help generate risk outputs that could be elucidated under different possibilistic levels. The proposed method could be used by environmental managers to evaluate trade-offs involving risks and costs, as well as identify management solutions that sufficiently hedge against dual uncertainties.

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Application of Optimal Control and Fuzzy Theory for Dynamic Groundwater Remediation Design

Cited by 37 publications

References 22 publications

Integration of Optimal Dynamic Control and Neural Network for Groundwater Quality Management

Integration of Optimal Dynamic Control and Neural Network for Groundwater Quality Management

A Fuzzy Inference System for the Conjunctive Use of Surface and Subsurface Water

Assessing environmental risks through fuzzy parameterized probabilistic analysis

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