این سایت در حال حاضر پشتیبانی نمی شود و امکان دارد داده های نشریات بروز نباشند
Analytical and Bioanalytical Electrochemistry، جلد ۱۶، شماره ۸، صفحات ۷۶۴-۷۸۵
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی Heavy Metals Potentiometric Sensitivity Prediction by Firefly-Support Vector Machine Modeling Method
چکیده انگلیسی مقاله The quantitative structure-property relationship (QSPR) method is an efficient and elegant method for estimating the critical parameters of a wide range of compounds. In this work, the QSPR data set included the structures of 45 modified diphenyl phosphoryl acetamide ionophores along with their sensitivity to Cd2+, Cu2+, and Pb2+. The data set was divided into the training set, including 36 compounds, and the test set, including 9 compounds. The stepwise -multiple linear regressions (SW-MLR), firefly multiple linear regressions (FA-MLR), and firefly-support vector machine (FA-SVM) models were produced on the training set with sensitivity of ionophores for Cd2+, Cu2+, and Pb2+ for predicting the potentiometric sensitivity of plastic polymer membrane sensors. The FA-SVM model showed good statistical results for all three cations. Internal and external validation was done to ensure the performance of the model. The results showed acceptable accuracy of the proposed method in identifying important descriptors in QSPR. The results of this study and the interpretation of the descriptors entered in the model can help to design new selective ligands.
کلیدواژه‌های انگلیسی مقاله Ion-selective electrode,heavy metals,QSPR,FireFly,Support Vector Machine
نویسندگان مقاله Eslam Pourbasheer |
Department of Chemistry, Faculty of Science, University of Mohaghegh Ardabili, P.O. Box 179, Ardabil, Iran

Reza Mahmoudzadeh Laki |
Department of Chemistry, Faculty of Science, University of Mohaghegh Ardabili, P.O. Box 179, Ardabil, Iran

Mohammad Sarafraz Khalifehlou |
Department of Chemistry, Faculty of Science, University of Mohaghegh Ardabili, P.O. Box 179, Ardabil, Iran

نشانی اینترنتی https://www.abechem.com/article_715433_37dbb98326b9888566e05deb7657d1f0.pdf
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده
برگشت به: صفحه اول پایگاه   |   نسخه مرتبط   |   نشریه مرتبط   |   فهرست نشریات