Using PCA and ANN in the explanation of groundwater chemism. Case of the Messaad Plateau. South Algerian Steppe Region

B. Rahmani, F. Bâali, C. Fehdi
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Abstract

The objective of this work is to study the chemistry of groundwater in the messaad plateau which is located 300km south of the capital of Algiers. The  results obtained showed that the waters are very strongly mineralized overall, with a predominance of calcium sulphate facies and calcium chloride  facies. a high degree of mineralization in the South and South-East part of the study area near Oued Messaad. The Principal Component Analysis (PCA)  has shown that the increase in mineralization is mainly due to the dissolution of evaporative mineral-rich salt-bearing formations. The hydro-chemical  model based on Artificial Neuron Networks (ANN) of the multilayer perceptron (MLP) type has shown that the SO4 2-,Cl- ,Ca2+,Na+ ions are the most  important factors influencing the electrical conductivity of water. These ions are the result of the dissolution of gypsum and halite continuously in the  clays and marls of the Barremian formations.
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用主成分分析和人工神经网络解释地下水化学。Messaad高原的案例。南阿尔及利亚大草原地区
这项工作的目的是研究位于首都阿尔及尔以南300公里的梅萨德高原的地下水化学。结果表明,该海域总体矿化程度很高,以硫酸钙相和氯化钙相为主。Oued Messaad附近研究区南部和东南部的高度矿化。主成分分析(PCA)表明,矿化度的增加主要是由于蒸发富矿物含盐地层的溶解。基于多层感知器(MLP)型人工神经元网络(ANN)的水化学模型表明,SO4 2-、Cl-、Ca2+、Na+离子是影响水电导率的最重要因素。这些离子是石膏和岩盐在Barremian地层的粘土和泥灰岩中持续溶解的结果。
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