Application of optimal control and fuzzy theory for dynamic groundwater remediation design

Hone Jay Chu; Liang-Jeng Chang

doi:10.1007/s11269-008-9293-1

Application of optimal control and fuzzy theory for dynamic groundwater remediation design

Hone Jay Chu, Liang-Jeng Chang^*

^*Corresponding author for this work

Department of Civil Engineering

Research output: Contribution to journal › Article › peer-review

38 Scopus citations

Abstract

Obtaining optimal solutions for time-varying groundwater remediation design is a challenging task. A novel procedure first employs input/output data sets obtained by constrained differential dynamic programming (CDDP). Then the Adaptive-Network-Based Fuzzy Inference System (ANFIS), which is a fuzzy inference system (FIS) implemented in the adaptive network framework, is applied to acquire time-varying pumping rates. Results demonstrate that the FIS is an efficient way of groundwater remediation design.

Original language	English
Pages (from-to)	647-660
Number of pages	14
Journal	Water Resources Management
Volume	23
Issue number	4
DOIs	https://doi.org/10.1007/s11269-008-9293-1
State	Published - 1 Jan 2009

Keywords

ANFIS
CDDP
Groundwater
Remediation design

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10.1007/s11269-008-9293-1

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Application of optimal control and fuzzy theory for dynamic groundwater remediation design

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Keywords

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