Prediction of Heavy Metal Removal by Different Liner Materials from Landfill Leachate: Modeling of Experimental Results Using Artificial Intelligence Technique
المؤلفون المشاركون
Turan, Nurdan Gamze
Gümüşel, Emine Beril
Ozgonenel, Okan
المصدر
العدد
المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-5، 5ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2013-06-10
دولة النشر
مصر
عدد الصفحات
5
التخصصات الرئيسية
الطب البشري
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
An intensive study has been made to see the performance of the different liner materials with bentonite on the removal efficiency of Cu(II) and Zn(II) from industrial leachate.
An artificial neural network (ANN) was used to display the significant levels of the analyzed liner materials on the removal efficiency.
The statistical analysis proves that the effect of natural zeolite was significant by a cubic spline model with a 99.93% removal efficiency.
Optimization of liner materials was achieved by minimizing bentonite mixtures, which were costly, and maximizing Cu(II) and Zn(II) removal efficiency.
The removal efficiencies were calculated as 45.07% and 48.19% for Cu(II) and Zn(II), respectively, when only bentonite was used as liner material.
However, 60% of natural zeolite with 40% of bentonite combination was found to be the best for Cu(II) removal (95%), and 80% of vermiculite and pumice with 20% of bentonite combination was found to be the best for Zn(II) removal (61.24% and 65.09%).
Similarly, 60% of natural zeolite with 40% of bentonite combination was found to be the best for Zn(II) removal (89.19%), and 80% of vermiculite and pumice with 20% of bentonite combination was found to be the best for Zn(II) removal (82.76% and 74.89%).
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Turan, Nurdan Gamze& Gümüşel, Emine Beril& Ozgonenel, Okan. 2013. Prediction of Heavy Metal Removal by Different Liner Materials from Landfill Leachate: Modeling of Experimental Results Using Artificial Intelligence Technique. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-5.
https://search.emarefa.net/detail/BIM-1011749
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Turan, Nurdan Gamze…[et al.]. Prediction of Heavy Metal Removal by Different Liner Materials from Landfill Leachate: Modeling of Experimental Results Using Artificial Intelligence Technique. The Scientific World Journal No. 2013 (2013), pp.1-5.
https://search.emarefa.net/detail/BIM-1011749
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Turan, Nurdan Gamze& Gümüşel, Emine Beril& Ozgonenel, Okan. Prediction of Heavy Metal Removal by Different Liner Materials from Landfill Leachate: Modeling of Experimental Results Using Artificial Intelligence Technique. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-5.
https://search.emarefa.net/detail/BIM-1011749
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1011749
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر