![]() ![]() Appl Math Comput 193(1):211–230ĭevaraj D, Yegnanarayana B (2005) Genetic-algorithm-based optimal power flow for security enhancement. In: Bentall, Ray, complier, Shortcuts and special problems in aquifer tests, US Geol Surv Water-Supply Pap:1545-Cĭeep K, Thakur M (2007) A new mutation operator for real coded genetic algorithms. Ground Water 19(3):275–278Ĭooper, HH Jr (1963) Type curves for nonsteady radial flow in an infinite leaky artesian aquifer. Environ Eng Geosci 19(3):253–263Ĭhander S, Kapoor PN, Goyal SK (1981) Analysis of pumping test data using Marquardt algorithm. Appl Soft Comput J 28:541–549īrown CJ (2013) Using solver to estimate aquifer parameters for non-leaky and leaky unsteady confined aquifer tests. Exp Math 14(3):317–329īateni SM, Mortazavi-Naeini M, Ataie-Ashtiani B, Jeng DS, Khanbilvardi R (2015) Evaluation of methods for estimating aquifer hydraulic parameters. J Hydrol 523(1–4):278–282īailey DH, Jeyabalan KS, Li XS (2005) A comparison of three high-precision quadrature schemes. Ground Water 30(2):164–166īaalousha HM (2015) Approximation of the exponential integral (well function) using sampling methods. Eng Appl Artif Intell 31:15–26Īziz ARA, Wong KV (1992) A neural-network approach to the determination of aquifer parameters. Our results indicate that our method is accurate, since the maximum relative error was found to be equal to 0.00036%, and practical, since it is free from special functions and could be easily incorporated within an optimization technique to analyze transient time-drawdown data.Īli M, Ahn CW, Siarry P (2014) Differential evolution algorithm for the selection of optimal scaling factors in image watermarking. Furthermore, a new full range numerical evaluation of the Hantush well function based on a tanh-sinh quadrature scheme has been proposed. For all analyzed pumping tests data, the differential evolution yielded the most accurate results with an improvement in SEE values ranged from 0.2 to 50% compared to previously published results, and exhibits speed and robustness. Both of the proposed metaheuristic algorithms provide accurate aquifer parameters. The standard error of estimate (SEE) was used as a performance criterion to evaluate the discrepancies between predicted and observed drawdown data in different pumping time periods. The proposed approaches combine metaheuristic algorithms with an appropriate analytical drawdown solution depending upon the nature of the considered aquifer system, leaky or naturally fractured rock aquifers. In this paper, an automatic interpretation of time-drawdown data has been proposed based on two algorithms, the real-coded genetic algorithm and differential evolution. It is traditionally performed in a subjective manner by means of standard type curves. Pumping tests data interpretation is of major importance in groundwater engineering. ![]()
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