A hybrid optimization approach for parameter estimation of confined and leaky confined aquifers

2019 ◽  
Vol 19 (8) ◽  
pp. 2359-2366 ◽  
Author(s):  
M. Tamer Ayvaz ◽  
Gurhan Gurarslan
Keyword(s):  
Parameter Estimation ◽  
Pumping Test ◽  
Hybrid Optimization ◽  
Optimization Approach ◽  
De Algorithm ◽  
Aquifer Parameter ◽  
Confined Aquifers ◽  
Estimation Problems ◽  
Reduced Gradient ◽  
Generalized Reduced Gradient

Abstract The main objective of this study is to propose a linked simulation–optimization approach for solving aquifer parameter estimation problems from pumping test results. In the simulation part of the proposed approach, the drawdowns at given monitoring points and times are calculated by considering the Theis and Hantush approaches for confined and leaky confined aquifers, respectively. This simulation part is then integrated to a newly proposed hybrid optimization approach, namely DE–Solver, which integrates the differential evolution (DE) algorithm and generalized reduced gradient (GRG) method of the spreadsheet Solver add-in. The performance of the proposed approach is evaluated by considering two pumping test data for confined and leaky confined aquifers. Identified results indicate that the proposed approach provides better results than those obtained by using different approaches in the literature.

scholarly journals Identification of the Aquifer Parameters from Pumping Test Data by Using a Hybrid Optimization Approach

10.29007/11v5 ◽  
2018 ◽  
Author(s):  
M. Tamer Ayvaz ◽  
Gurhan Gurarslan
Keyword(s):  
Test Data ◽  
Harmony Search ◽  
Pumping Test ◽  
Hybrid Optimization ◽  
Optimization Approach ◽  
Confined Aquifers ◽  
Reduced Gradient ◽  
Generalized Reduced Gradient ◽  
The Given ◽  
Search Capability

The main objective of this study is to propose a linked simulation-optimization approach to determine the parameters of the confined and leaky-confined aquifers from the results of the pumping tests. In the simulation part of the proposed approach, the drawdowns at the given monitoring points and times are calculated by considering Theis and Hantush approaches for confined and leaky-confined aquifers, respectively. This simulation part is then integrated with a hybrid optimization approach where global exploration feature of the harmony search (HS) and strong local search capability of the generalized reduced gradient (GRG) approach of the spreadsheet Solver add-in are mutually integrated. The performance of the proposed approach is evaluated by considering two pumping test data for the confined and leaky-confined aquifers. Identified results indicated that the hybrid HS-Solver optimization approach provides better results than those obtained by using both curve matching and stand-alone HS approaches.

scholarly journals A hybrid optimization approach for automated parameter estimation problems

PAMM ◽  
2007 ◽  
Vol 7 (1) ◽  
pp. 1062507-1062508 ◽  
Author(s):  
M. Argáez ◽  
H. Klie ◽  
C. Quintero ◽  
L. Velázquez ◽  
M. Wheeler
Keyword(s):  
Parameter Estimation ◽  
Hybrid Optimization ◽  
Optimization Approach ◽  
Estimation Problems

Optimal Design of Mechanical Components With Sizing, Configurational and Topological Consideration

1989 ◽  
Author(s):  
E. Sandgren ◽  
H. Lee ◽  
M. El-Sayed
Keyword(s):  
Optimal Design ◽  
Frame Structure ◽  
Optimization Approach ◽  
Reduced Gradient Method ◽  
Beam Elements ◽  
Reduced Gradient ◽  
Mechanical Components ◽  
Upper Level ◽  
Generalized Reduced Gradient ◽  
Seat Frame

Abstract A methodology for the optimal design of structural mechanical components with sizing, configurational and topological consideration is presented. The optimization involves the minimization of structural weight subject to stress and deflection constraints. A finite element code with internally generated design sensitivities and general element connectivities is implemented in order to solve for the stresses and deflections in the structure. Beam elements with various crossectional configurations are considered. The generalized reduced gradient method is applied to solve the constrained nonlinear programming problem. A hierarchical design optimization approach is taken with topological issues considered at the upper level and geometric and crossectional issues considered at the lower level. An example involving the design of an automotive seat frame structure is presented to demonstrate the approach.

scholarly journals Parameter Estimation of Ion Current Formulations Requires Hybrid Optimization Approach to Be Both Accurate and Reliable

2016 ◽  
Vol 3 ◽  
Author(s):  
Axel Loewe ◽  
Mathias Wilhelms ◽  
Jochen Schmid ◽  
Mathias J. Krause ◽  
Fathima Fischer ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Ion Current ◽  
Hybrid Optimization ◽  
Optimization Approach

Parameter estimation of an improved nonlinear Muskingum model using a new hybrid method

2016 ◽  
Vol 48 (5) ◽  
pp. 1253-1267 ◽  
Author(s):  
Majid Niazkar ◽  
Seied Hosein Afzali
Keyword(s):  
Parameter Estimation ◽  
Evaluation Criteria ◽  
Variable Parameter ◽  
Optimization Techniques ◽  
Flood Routing ◽  
Gradient Algorithm ◽  
Hybrid Technique ◽  
Muskingum Model ◽  
Reduced Gradient ◽  
Generalized Reduced Gradient

Although various techniques have been proposed to estimate the parameters of different versions of the Muskingum model, more rigorous techniques and models are still required to improve the computational precision of the calibration process. In this research, a new hybrid technique was proposed for Muskingum parameter estimation. Based on the conducted comprehensive literature review on the Muskingum flood routing models, a new improved Muskingum model with nine constant parameters was presented. Since the inflow-weighted parameter in the proposed model is a function of inflow hydrograph, it varies during the flood period and consequently can also be considered as a variable-parameter Muskingum model. The new hybrid technique was successfully applied for parameter estimation of the new version of Muskingum model for two case studies selected from the literature. Results were compared with those of other methods using several common performance evaluation criteria. The new Muskingum model significantly reduces the sum of the square of the deviations between the observed and routed outflows (SSQ) value for the double-peak case study. Finally, the obtained results indicate that not only the hybrid modified honey bee mating optimization-generalized reduced gradient algorithm somehow overcomes the shortcomings of both zero and first-order optimization techniques, but also the new Muskingum model appears to be the most reliable Muskingum version compared with the other methods considered in this study.

scholarly journals Set-membership identifiability of nonlinear models and related parameter estimation properties

2016 ◽  
Vol 26 (4) ◽  
pp. 803-813 ◽  
Author(s):  
Carine Jauberthie ◽  
Louise Travé-MassuyèEs ◽  
Nathalie Verdière
Keyword(s):  
Mathematical Model ◽  
Parameter Estimation ◽  
Dynamic System ◽  
Nonlinear Models ◽  
Differential Algebra ◽  
Related Parameter ◽  
Set Membership ◽  
Estimation Problems ◽  
The Mathematical Model

Abstract Identifiability guarantees that the mathematical model of a dynamic system is well defined in the sense that it maps unambiguously its parameters to the output trajectories. This paper casts identifiability in a set-membership (SM) framework and relates recently introduced properties, namely, SM-identifiability, μ-SM-identifiability, and ε-SM-identifiability, to the properties of parameter estimation problems. Soundness and ε-consistency are proposed to characterize these problems and the solution returned by the algorithm used to solve them. This paper also contributes by carefully motivating and comparing SM-identifiability, μ-SM-identifiability and ε-SM-identifiability with related properties found in the literature, and by providing a method based on differential algebra to check these properties.

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