Evolving genetic programming and other AI-based models for estimating groundwater quality parameters of the Khezri plain, Eastern Iran

Aryafar, Ahmad; Khosravi, Vahid; zarepourfard, Hosniyeh; Rooki, Reza

doi:10.1007/s12665-019-8092-8

Cited by 39 publications

(9 citation statements)

References 43 publications

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“…The study also showed that the SVM model is a fast, reliable, and cost-effective AI technique. The feasibility of AI techniques in groundwater quality simulation has been evaluated by numerous scholars and such studies have produced efficient performances [32][33][34][35][36][37][38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Development of artificial intelligence models for well groundwater quality simulation: Different modeling scenarios

Shiri

Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

et al. 2021

PLoS ONE

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Groundwater is one of the most important freshwater resources, especially in arid and semi-arid regions where the annual amounts of precipitation are small with frequent drought durations. Information on qualitative parameters of these valuable resources is very crucial as it might affect its applicability from agricultural, drinking, and industrial aspects. Although geo-statistics methods can provide insight about spatial distribution of quality factors, applications of advanced artificial intelligence (AI) models can contribute to produce more accurate results as robust alternative for such a complex geo-science problem. The present research investigates the capacity of several types of AI models for modeling four key water quality variables namely electrical conductivity (EC), sodium adsorption ratio (SAR), total dissolved solid (TDS) and Sulfate (SO4) using dataset obtained from 90 wells in Tabriz Plain, Iran; assessed by k-fold testing. Two different modeling scenarios were established to make simulations using other quality parameters and the geographical information. The obtained results confirmed the capabilities of the AI models for modeling the well groundwater quality variables. Among all the applied AI models, the developed hybrid support vector machine-firefly algorithm (SVM-FFA) model achieved the best predictability performance for both investigated scenarios. The introduced computer aid methodology provided a reliable technology for groundwater monitoring and assessment.

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Section: Introductionmentioning

confidence: 99%

Development of artificial intelligence models for well groundwater quality simulation: Different modeling scenarios

Shiri

Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

et al. 2021

PLoS ONE

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“…Hydrology: Hydrology is a branch of water science that widely needs predictions models. GP was widely used in hydrology applications such as precipitation prediction and measurement [123], Rainfall-Runoff modeling [124][125] groundwater quality prediction [126], evapotranspiration estimation [127] etc. A comprehensive review study focuses on GP applications in the field of hydrology [128].…”

Section: Urbanization and Buildingmentioning

confidence: 99%

A Review of Genetic Programming: Popular Techniques, Fundamental Aspects, Software Tools and Applications

Ari

Alagöz

2021

Sakarya University Journal of Science

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Genetic Programming (GP) is one of the evolutionary computation (EC) methods followed with great interest by many researchers. When GP first appeared, it has become a popular computational intelligence method because of its successful applications and its potentials to find effective solutions for difficult practical problems of many different disciplines. With the use of GP in a wide variety of areas, numerous variants of GP methods have emerged to provide more effective solutions for computation problems of diverse application fields. Therefore, GP has a very rich literature that is progressively growing. Many GP software tools developed along with process of GP algorithms. There is a need for an inclusive survey of GP literature from the beginning to today of GP in order to reveal the role of GP in the computational intelligence field. This survey study aims to provide an overview of the growing GP literature in a systematic way. The researchers, who need to implement GP methods, can gain insight of potentials in GP methods, their essential drawbacks and prevalent superiorities. Accordingly, taxonomy of GP methods is given by a systematic review of popular GP methods. In this manner, GP methods are analyzed according to two main categories, which consider the discrepancies in their program (chromosome) representation styles and their methodologies. Besides, GP applications in diverse problems are summarized. This literature survey is especially useful for new researchers to gain the required broad perspective before implementing a GP method in their problems.

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“…In addition, the correlation between any parameters is another important investigation in order to understand their relationships. It can be conducted through various methods, e.g., genetic programming (GP) [32], linear regression [33], correlation coefficient matrix [19,20], etc. In this study, the correlation between various parameters of Preal commune aquifer was calculated which is presented in Table 13.…”

Section: Statistical Analysis Of Groundwater Qualitymentioning

confidence: 99%

A Survey of Household Water Use and Groundwater Quality Index Assessment in a Rural Community of Cambodia

et al. 2021

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To propose an efficient system for addressing water scarcity in a rural area through groundwater use, the information on water consumption and interpretation of groundwater quality are essential for estimating the optimal preparation of the comprehensive water system. Hence, this study aimed to estimate the current household domestic water consumption and groundwater quality index of currently accessed wells in a small rural community of Preyveng province, Cambodia as a practical and beneficial as well as a model for the water resource sector in rural areas. The questionnaire survey was designed as the main instrument for collecting the household water use as face-to-face interviews. The result showed that the average daily water consumption in the Preal commune is about 71 L per capita, which is almost two times lower than the minimum water quantity recommended by the World Health Organization (WHO), 150 L/day per capita. Moreover, 100% of the households in this commune heavily rely on groundwater wells for domestic water use and more than 50% confirmed that they used raw groundwater as drinking water without a proposer treatment system. Approximately 70% of the people in Preal wishes to have a clean water supply and more than 80% of the household had a positive willingness to pay for clean water supply. In terms of groundwater quality in the Preal commune, it is mainly contaminated by iron, arsenic, fluoride, and manganese, which are mainly associated with human health effects from daily consumption. About 75% of groundwater wells are presented in poor conditions and were unsuitable for drinking purposes. Lastly, the suitable water treatment and supply should be considered in order to reduce the effects on people’s health as well as to improve living conditions.

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Evolving genetic programming and other AI-based models for estimating groundwater quality parameters of the Khezri plain, Eastern Iran

Cited by 39 publications

References 43 publications

Development of artificial intelligence models for well groundwater quality simulation: Different modeling scenarios

Development of artificial intelligence models for well groundwater quality simulation: Different modeling scenarios

A Review of Genetic Programming: Popular Techniques, Fundamental Aspects, Software Tools and Applications

A Survey of Household Water Use and Groundwater Quality Index Assessment in a Rural Community of Cambodia

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