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Soft computing techniques in prediction Cr(VI) removal efficiency of polymer inclusion membranes
Muhammad Yaqub,Beytullah EREN,Volkan Eyupoglu 대한환경공학회 2020 Environmental Engineering Research Vol.25 No.3
In this study soft computing techniques including, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were investigated for the prediction of Cr(VI) transport efficiency by novel Polymer Inclusion Membranes (PIMs). Transport experiments carried out by varying parameters such as time, film thickness, carrier type, carier rate, plasticizer type, and plasticizer rate. The predictive performance of ANN and ANFIS model was evaluated by using statistical performance criteria such as Root Mean Standard Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R<SUP>2</SUP>). Moreover, Sensitivity Analysis (SA) was carried out to investigate the effect of each input on PIMs Cr(VI) removal efficiency. The proposed ANN model presented reliable and valid results, followed by ANFIS model results. RMSE and MAE values were 0.00556, 0.00163 for ANN and 0.00924, 0.00493 for ANFIS model in the prediction of Cr(VI) removal efficiency on testing data sets. The R2 values were 0.973 and 0.867 on testing data sets by ANN and ANFIS, respectively. Results show that the ANN-based prediction model performed better than ANFIS. SA demonstrated that time; film thickness; carrier type and plasticizer type are major operating parameters having 33.61%, 26.85%, 21.07% and 8.917% contribution, respectively.
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Heavy metal profiles of agricultural soils in Sakarya, Turkey
Mehmet Isleyen,Aysegul Akpinar,Beytullah Eren,Gulsun Ok 대한환경공학회 2019 Environmental Engineering Research Vol.24 No.3
Sakarya is famous for cucurbit productions in Turkey and cucurbits can grow as big as 560 kg of weight per fruit in its agricultural areas. There is no or limited information about contaminant levels and profiles of the agricultural fields in Sakarya. The purpose of this study is to investigate the levels of polycyclic aromatic hydrocarbons (PAHs) (naphthalene, phenanthrene, pyrene, and fluoranthene) and heavy metal (As, Cd, Cu, Cr, Ni, Pb, Zn) concentrations of the selected fields. Total 33 soil samples were collected from 12 counties of Sakarya where both cucurbits have been produced and organochlorine pesticides have been applied to the fields for more than 30 y during the historical plantation periods. Heavy metal and PAH contents in the soil samples were measured by an Inductively Coupled Plasma Emission Spectroscopy and a Gas Chromatography-Mass Spectrometry. The highest phenanthrene, pyrene, and fluoranthene concentrations were measured as 63.50 ng/g, 134.34 ng/g, 140.0 ng/g, respectively in the soil samples from Geyve County. Cu, Ni, and Cr concentrations were measured as 108.2 ㎎/㎏, 219.9 ㎎/㎏, and 173.1 ㎎/㎏, respectively in Geyve’s samples which were also the highest and 2-7 times more than the limit values given in the Turkish Soil Pollution Control Regulation. Precautions need to be taken for Sakarya’s agricultural fields which are an important milestone of Turkey’s cucurbit and fruit productions since the contaminants can be accumulated in the fruits and edible parts of the plants.
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